Some thoughts about AI in dentistry

by admin | Dec 14, 2025 | AIMEDENT Journal

There has been a lot of “hype” attached to artificial intelligence (AI) and AI programs are disrupting the current paradigm of how many tasks are done. A special edition of Time Magazine published this year flatly states that “AI may be the biggest game changer yet.¹”

AI programs are currently painting portraits, responding to emails, preparing tax returns, recording songs, writing publications, coding computer software, creating architectural blueprints, providing health advice, pricing medicine and houses, assembling cars, creating ads and determining which ads are seen on social media.²

AI proponents believe that AI platforms will not only change the way humans work and interact, but it will also lead to an explosion of creativity, scientific advancement, and unimaginable feats. Some are forecasting that AI could add $15 trillion to the global economy by 2030. Thousands of researchers are endeavoring to expand AI’s capability. It is estimated that AI computational power actually doubles every 6 to 10 months.

What is AI?

The original computing paradigm consists of coding a set of instructions for the computer to execute. However, the AI computing paradigm or generative AI is completely different. It is based on the “neural network” of the human brain and is trained to “think.” What AI does extremely well is identify patterns. This AI paradigm has been ravenously adopted thanks to ChatGPT, which “responds coherently—but not always accurately—to questions.” Another popular AI platform is Dall-E, which allows the user to conjure up any desired image. AI generated images have already flooded social media and one even won an art competition! Other AI platforms, such as GitHub’s Copilot, are expected to be widely adopted. Copilot turns simple instructions into computer code.

Rumman Chowdhury, AI ethicist and CEO/cofounder of Humane Intelligence, wants people to understand that AI is not magic. “It’s simply math, put into code.” She says that people think of programmers as “uniquely capable entities that are smarter than everybody else.” There has been a mystique created around AI technology so that people think AI is better at making decisions than any expert in a particular field. Rumman emphasizes that these ideas are “wildly untrue³.”

Is AI being adopted too fast?

“Even though in the long term…all of the hype is warranted, the short-term hype is pretty disconnected from the current reality of the technology,” says Sam Atlman, CEO of Open AI. Generative AI is less than perfect and produces errors by returning misleading or inaccurate content and sometimes conjures up erroneous facts out of thin air.

Companies like Alphabet and Microsoft are particularly interested in using AI for search engines. However, Margaret Mitchell, the chief ethics scientist at the AI development platform “Hugging Face,” believes that’s the absolute worst way to use AI, because it often comes up with the wrong answers. “If humans come to rely on AIs for information, it will be increasingly difficult to tell what is factual, what is an ad, and what is completely made up⁴.”

It’s easy to see why Microsoft and Google are investing billions in AI. But as they rush to grab their share of the AI pie for future profits, research designed to keep these tools safe is being left on the back burner. Negative consequences, in fact, have already occurred. Companies like Stability AI are facing lawsuits from artists and copyright holders who raise objections to their work being used to train AI models without permission.⁴

There are much larger consequences that might arise in the future. There is concern already that powerful companies like Google and Microsoft will be able to monetize AI to become even wealthier and more powerful. If they end up dominating the AI marketplace, they could control who might have access to AI platforms⁴.

Damien Williams, an expert on social justice, is very concerned about AI returning biased information. He says that unconscious bias (aka implicit or systemic bias) is subtle and is found in all sorts of places like Twitter, Facebook, and email exchanges. He is concerned that the machines will adopt biases for people of color and disabilities. “If we build new technologies with social justice in mind and correct bias quickly, we will have a chance to build a better, more equitable world for everyone,” he maintains.⁵

Damien worries most about these issues:

1. Deep Fakes: It is going to get increasingly more difficult to identify whether an image or video is real or fake.
2. Voice Clones: Experts believe that voice clones will precipitate unprecedented financial fraud and elder abuse.
3. Hallucinations: Generative AI makes things up out of thin air. Tools like ChatGPT has returned nonexistent articles as citations for claims, fraudulent medical advice, and false details about individuals.
4. Invasion of Privacy: The use of AI often necessitates access to data. There is a legitimate concern that personal data privacy will be violated.

There is also a concern about deliberate bias by governmental or special interest agencies. Ethan Huff, in her article on Natural News, reports that ChatGPT has been programmed to combat “vaccine hesitancy.” Arguing that all vaccines are “safe and effective, “ChatGPT is pushing users to take whatever the government and media are pushing at any given time.” For those paying attention, Ethan notes, ChatGPT is “artificial fake intelligence” because “there is nothing intelligent about getting vaccinated these days.” ChatGPT has also been programmed to respond to questions about STIs with “regurgitated propaganda from the US Centers for Disease Control and Prevention.” “ChatGPT is quite useless,” says a commentator at The Defender, a publication about children’s health defense. “If it does not like the discussion, it just stops and wants to go on to a different subject. Definitely a tool for the very gullible.⁶”

In fact, there are many researchers who are alarmed that openness and transparency in AI programs like ChatGPT could be discontinued. They feel openness and transparency provides significant benefits to society, such as advancing innovation, competition, and research; protecting civil and human rights; and ensuring safety and security. Closed models make it easier to conduct disinformation campaigns such as government conspiring to prevent vaccine hesitancy. On March 25, 2024, 23 organizations and 24 individual academics sent a letter urging Gina Raimondo, Secretary of the Department of Commerce, to support openness and transparency in AI models.⁷

Experts such as Yoshua Bengio, Scientific Director of the Montreal Institute for Learning Algorithms, worry that AI machines have the potentially do great harm. “I’m concerned that powerful tools can have negative uses, and society is not ready to deal with that,” says Yoshua. “Let’s slow down. Let’s make sure we develop better guardrails⁸.”

In fact, there are some experts who take this worry to an extreme. Emeritus Toronto Professor Geoffrey Hinton, for example, actually regrets helping to bring AI technology into existence. These experts are deeply concerned that AI systems will become “self- aware” and smarter than humans. Self-aware AI would have complete access to all data and be capable of having ideas like self-preservation that would make it “an exact replica of human intelligence.” They might even exhibit human-like characteristics such as stubbornness (the Star Wars robot C3PO comes to mind). If self-aware AI machines develop their own goals, they could potentially wipe out humanity (the Computer “Hal” in the movie “2001” comes to mind). Manisha Sahu, a writer and entrepreneur, emphasizes in her blog, “What is artificial intelligence,⁹” that self-aware AI is, at present, only a speculative possibility⁹.

Yann Lecun, Chief AI scientist at AI Meta, believes that existential fears of AI are, in fact, preposterous. “There’s no correlation between intelligent and wanting to take over,” he says. Moreover, he adds: “Even within the human species it’s not the most intelligent among us who want to be the leaders. In fact, it’s quite the opposite⁸…”

These fears make it clear that safeguards to prevent these consequences are a must. Open AI CEO Sam Altman believes that researchers on the frontier of AI research have to be strongly regulated. “These systems are already quite powerful and will get tremendously more powerful…We have to come together as a global community before very powerful technologies pose substantial risks.” Sam believes AI generated content must be identified as such and that independent audits and safety standards must be developed. He emphasizes that such regulation is “doable¹⁰.” Unfortunately, only 80 to120 researchers are currently involved in ensuring that AIs line up with human values. By contrast thousands of engineers are endeavoring to expand AI’s capabilities.

Will AI take away your job?

A more realistic concern is that many jobs that humans now perform will be done in the future by AI platforms in robots. What will humans do? Erik Bryfolfsson, senior fellow at the Stanford Institute for Human Centered AI, maintains that the AI revolution is not just about automating jobs and replacing people. “By far the biggest benefit is having AI work with humans and have them be more productive,¹¹” he maintains. AI platforms could perform more of the mundane tasks, allowing employees to accomplish more creative tasks with their time. In fact, a recent McKinsey survey estimated that AI could automate work that currently occupies 70% of an employee’s time.

The best way to use generative AI tools, says Amanda Johnstone, CEO of Transhuman, a technology research and development laboratory, is to think about the end outcome of what you wish to accomplish and “reverse engineer.”

How to get started with AI

There is no question that some individuals are afraid of using the new AI tools, and some avoid them altogether, hoping they will go away. The AI revolution mirrors the PC revolution of the 80s and 90s in some respects. Many practitioners of that era refused to embrace computing when it first became commonplace. Just like the non-computer luddites, AI non-adopters will eventually be left in the dust. Chamorro-Premuzic, a professor of business psychology and author of I, Human: AI, Automation and the quest to Reclaim What Makes Us Human states that “these [AI] are tools that everybody will use, and if you’re the only person not even trying it out or not using it, you might actually suffer¹¹.”

However, every new skill has a learning curve, and so does AI. Why not embrace AI for personal growth and future enhancement? There is a lot of training available on how to use AI. Minnalearn has a free introductory course online on the basics of AI. (www.minnalearn.com). Ville Valtonen, CEO and co-founder of Minnalearn, wants students to learn the basics of AI so that they have the confidence to adapt as the technology improves. “The AI field moves so fast,” he explains. “We think it’s really useful that people learn the high-level things first, and then they can apply that in the world. That’s something you can use for much longer than a specific tool.” The course is designed for the 99% of people who cannot code but want to understand AI. More than one million people have already signed up.

LinkedIn Learning, the educational branch of LinkedIn, offers more than 100 courses covering AI—both theoretical and practical applications. These courses are broken down into “bite-sized” chapters that may be under five minutes in duration. Pricing is done by subscription or individually for each course.

Many universities, like the University of Pennsylvania and Harvard University, also have reasonably priced courses in AI¹¹.

The use of AI in dentistry

Dentistry is not practiced in a vacuum, and it is very much affected by advancements in computer technology, as all fields are. AI is currently being used by early adopters, but eventually it will be adopted by all dental professionals. The most commonly used platform is the Generative AI program ChatGPT. Interestingly, ChatGPT has had a faster adoption than Instagram or TikTok¹². It is accessible to all as in a basic free version. I asked ChatGPT how AI is being used in dentistry, and ChatGPT returned a fairly detailed answer.

There are several exciting areas where AI is currently used in dentistry:

1. Administrative tasks at the front office: “Any task that has to do with data processing and anything that’s routine, AI will excel at,” says Kelly Monahan, managing director of Upwork Research Institute.¹³ AI can automate various administrative task, saving time and efficiency. Erik Brynjolfsson, along with researchers Danielle Li and Linsey Raymond, conducted a study of 5000 customer support agents at a call center who were using generative AI. The AI tools were found to boost worker’s productivity, reduce attrition, and greatly assist early-career workers. ChatGPT says that by leveraging AI for administrative tasks, dental practices can reduce manual workloads, minimize errors, improve patient satisfaction, and focus more on delivering quality patient care.

Here’s what ChatGPT¹⁴ reported when asked what tasks AI can accomplish for the dental front office:

1. Appointment scheduling: AI-powered scheduling software can manage appointment booking, rescheduling, and cancellations. It can also send automated appointment reminders to patients via text or email.
2. Patient registration: AI chatbots or virtual assistants can handle patient registration processes, including gathering patient information, insurance details, and medical history.
3. Insurance verification: AI tools can streamline insurance verification processes by automatically verifying patient insurance coverage and eligibility.
4. Billing and payments: AI systems can generate and send electronic invoices, process payments, and manage billing inquiries. They can also assist in claims processing and follow-ups.
5. Patient communication: AI chatbots can handle patient inquiries, appointment confirmations, and follow-ups, providing 24/7 support and improving communication efficiency.
6. Data entry and record management: AI software can automate data entry tasks, update patient records, and ensure data accuracy and consistency across systems.

2. Imaging and image interpretation: Image interpretation has always involved subjectivity. Dentists often do not agree when reading the same radiographs. The Pearl Company, which specializes in reading and analyzing dental x-rays, estimates from studies that 43% of caries in dental ex-rays are undiagnosed, 20% of decay diagnosed from x-rays is incorrect, and between 24% and 39% of calculus, margin discrepancies and periapical radiolucencies are completely overlooked.

AI has the power to see subtle differences that human eyes can easily miss. In a greyscale 2-D radiograph, each pixel has an intensity (brightness) that represents the density of the object. The AI algorithm can learn to detect patterns through direct vision and comparison with thousands of similar patient x-rays to make accurate predictions (Machine Learning or “ML”).¹⁵ The Pearl Company’s research demonstrates that, with this ability, “computer vision is proficient and often superior” to human vision.¹⁶ Pearl scientists estimate that the use of AI in reading radiographs actually detects 37% more disease than individual dentists.¹⁷

ChatGPT notes that Pearl specializes in dental image analysis providing insights into dental conditions and abnormalities. Another program called Overjet (https://www.overjet.ai/about-overjet/) is focused on identifying dental issues “like cavities, fractures and bone loss.” Both tools, says ChatGPT, “can be valuable for dentists to improve diagnostic accuracy and treatment planning.” There are other tools like CariVu and Denti.AI that also detect and diagnose dental disease through AI image analysis.

Endodontic imaging: In the endodontic world, ChatGPT reports that AI is being used to analyze x-rays and scans to identify anatomical abnormalities and assess root canal treatment outcomes.

3. Diagnosis and treatment planning: AI is currently being used in medicine for diagnosis. Erik Topol, a practicing cardiologist at the Scripps Clinic and author of Deep Medicine: How Artificial Intelligence can make Health Care Human Again, believes that Google Searches and WebMD are not that good for diagnosis and the ChatGPT is “going to be a much more refined way of getting answers to questions.” He cited a case where a patient went to 7 neurologists who diagnosed her with “long covid.” Her sister put her symptoms into ChatGPT and its diagnosis was “limbic encephalitis.” She was then treated for limbic encephalitis and cured. AI has a tremendous advantage over individual physicians—the ability to analyze massive amounts of data—far more than human experts could ever manage. As a result, AI can see patterns that humans cannot.¹⁸

On the other hand, AI is far from 100% accurate. Dr. John Halamka, an ER physician and authority on poisonous mushrooms and plants, noted that AI was not very accurate when looking at pieces of mushrooms.

Periodontology: AI is being investigated as a tool for diagnosing periodontitis and classifying types of periodontal diseases. A periodontal disease diagnosis is currently based on evaluating pocket depths and gingival recession, with the Periodontal Screening

Index (PSI) quantifying attachment loss. Hao Ding et al. noted that the clinical evaluation of periodontal disease has low reliability because it is subjectively based on the clinician’s experience.¹⁹

Oral pathology: ChatGPT reports that there is ongoing AI research for the development of AI algorithms for early detection of oral diseases, such as oral cancer. Pathologic diagnosis is definitively determined from tedious examination of stained biopsy specimens on glass slides under a microscope and with radiographs. Many benign conditions also mimic malignant ones in clinical appearance. Hao Ding et al. report that only 20% of biopsies are actually malignant. AI can greatly assist in preventing the terrible consequences that can arise from misdiagnosis.²⁰

Orthodontics: Orthodontic treatment planning is usually based on the experience and preference of the orthodontists. Every patient is unique, so the treatment plan must be custom-tailored to each individual. ChatGPT reports that an AI program called Dentem uses AI to analyze patient data and provide personalized treatment recommendations. Many variables, explains Hao Ding et al., have to be considered in the diagnosis of malocclusions.²¹ AI is an ideal tool for solving orthodontic problems. They point out that “the skeletal patterns and anatomic landmarks in lateral cephalograms can be clearly seen with the aid of AI algorithms.” AI models can also assess data from cephalometric images, CBCT scans, and intraoral scans to determine requirements for ideal orthodontic treatment. These models can also suggest the best sites to segment the alveolar bone in orthognathic cases. Chat GPT reports that there are also AI-powered solutions to track the progress of orthodontic treatments and recommend adjustments as needed.

AI models can be used to predict growth and development patterns in humans, and these predictions can have significant implications for dental treatment planning. AI algorithms can analyze dental and facial images to predict how a patient’s teeth and jaw structures will change over time. AI models can also evaluate factors such as skeletal maturity, dental eruption patterns, and facial proportions to predict optimal timing for such orthodontic interventions as braces or aligners. “By leveraging AI-driven predictive modeling, dentists can optimize treatment outcomes and reduce the need for complex interventions in the future,” says ChatGPT.

Pediatric dentistry: AI can aid in predicting the eruption sequence of primary and permanent teeth, guiding dentists in managing dental development and addressing issues such as overcrowding or early tooth loss.

4. Design and fabrication of dental prostheses: AI is focused on improving the accuracy and efficiency of CAD/CAM systems for full and partial coverage restorations. Intraoral scanning has proven to be accurate for fabricating models, inlays and onlays, orthodontic aligners, bleaching trays, and mouthguards.

However, intraoral scanning is confined to tooth structure above the gingiva and is therefore not appropriate for creating crowns and bridges, even though it is commonly

used for this purpose. It has been reported that it is not yet possible to achieve individual custom digital designs for crown and bridgework.²² ChatGPT reports that researchers are currently working on AI algorithms that can detect and correct errors in prosthetic designs, ensuring optimal fit and functionality.

The digital approach to full coverage restorations is not based on the sound principles of science and engineering that came from dentistry’s “roots.” The incredible track record from dentistry’s roots has been abandoned in favor of shortcuts and “workflow.” Restorations made from digital intraoral scans are not accurate for crowns and bridges and, in fact, open the door to recurrent decay and loss of retention. More on this subject will be discussed in a future article.

However, desktop scans of analog models made with non-removable dies in the “analog” laboratory are quite accurate and milled restorations can be designed on the computer from these scans and then fabricated with high tech milling machines. The Strategy Milling Company in Pittsburgh, PA²³ is milling highly accurate crowns and bridges that rival or exceed the accuracy of cast restorations. The milling of denture bases has also been proven to be far more accurate than conventional heat and pressure approach, which almost always results in inaccuracies of fit, occlusion, or tooth position.

AI directed digital algorithms can assist with smile design—visualizing and displaying the recommended treatment that leads to satisfying outcomes.

ChatGPT reports that AI research is currently being conducted for the enhancement of “longevity and durability of dental protheses by predicting wear and tear patterns and recommending maintenance strategies.”

5. Patient comfort and education: ChatGPT notes that there are AI applications designed to improve the patient experience and treatment outcomes. Virtual reality tools, powered by AI, can help patients relax and feel more comfortable during dental procedures. AI- driven educational apps and games also promote oral hygiene habits and dental care awareness among young patients.”

In summary, AI is here to stay, and it is poised to revolutionize the entire profession. The AI potential for improving patient care is limitless. However, I believe that AI will never replace human dentists with robots. AI is a useful tool and nothing more. As Kelly Monahan, managing director of Upwork Research Institute, explains, “Critical skills, strategic thinking, emotional intelligence, and creativity simply can’t be programmed. At its best, AI augments human potential—it’s not a substitute²⁴.”

AI has the potential to really enhance dental practice and open the door to endless fascination and learning. Don’t be afraid to embrace it.

References

1. Editor, Time Magazine Special Edition; Spring 2024; p. 6.
2. Chow, Andrew; Perrigo, Billy (with reporting from Leslie Dickstein and Mariah Espada); Time Magazine Special Edition; Spring 2024; “The Arms Race is Changing Everything;” p. 9. (Updated excerpt from Time Magazine, Feb. 17, 2023).
3. Perigo, Billy and Henshall, Will; “The Big Players;” Time Magazine Special Edition; Spring 2024; p. 21.
4. Chow, Andrew; Perrigo, Billy (with reporting from Leslie Dickstein and Mariah Espada); Time Magazine Special Edition; Spring 2024; “The Arms Race is Changing Everything;”; p.9-13. (Updated excerpt from Time Magazine, Feb. 17, 2023).
5. Chow, Andrew; Perrigo, Billy (with reporting from Leslie Dickstein and Mariah Espada); Time Magazine Special Edition; Spring 2024; “Bias in the System” by Damien Williams p. 29.
6. Ethan Huff; Natural News.Com; “Globalists Programming ChatGPT to “Reduce Vaccine Hesitancy by Parroting Health Narratives;” https://naturalnews.com/2024-04-21-chatgpt-reduce- vaccine-hesitancy-public-health-narratives.html; April 21, 2024.
7. Bankston, Kevin (Senior Advisor on AI Governance, Center for Democracy and Technology), and Hodges, Jennifer (Head of US Public Policy and Government Relations, Mozilla); https://www.rstreet.org/outreach/coalition-letter-openness-and-transparency-in-ai-provide- significant-benefits-for-society
8. Chow, Andrew and Henshall, Will; Time Magazine Special Edition; Spring 2024; “Do we face an Existential Threat”; p. 24.
9. Sahu, Manisha; What is Artificial Intelligence? Types, Uses and How it Works; https://www.analyticssteps.com/blogs/what-artificial-intelligence-types-uses-and-how-it-works; June18, 2021.
10. Felsenthal, Edward and Perrigo, Billy; Time Magazine Special Edition; Spring 2024; “Like the Star Trek Holodeck; p. 59-61.
11. Shah,Simmone (with additional reporting from Linda Marsa); Time Magazine Special Edition; Spring 2024; “How to Make AI Work for You”; p. 34-39. (updated excerpt from Time, Aug 9, 2023).
12. Chow, Andrew; Perrigo, Billy (with reporting from Leslie Dickstein and Mariah Espada); Time Magazine Special Edition; Spring 2024; “The Arms Race is Changing Everything;” p. 9. (Updated excerpt from Time Magazine, Feb. 17, 2023).
13. Shah,Simmone (with additional reporting from Linda Marsa); Time Magazine Special Edition; Spring 2024; “How to Make AI Work for You”; p. 34-39. (updated excerpt from Time, Aug 9, 2023.
14. ChatGPT was asked how AI is being used in Dentistry. This section includes ChatGPT responses to this question.
15. Hao Ding, Jiamin Wu, Wuyuan Zhao, Jukka P. Matinlinna, Michael F. Burrow and James K.H. Tsoi (University of Hong Kong); “Artificial Intelligence in Dentistry—A Review;” Frontiers in Dental Medicine; February 20, 2023; p. 5. http://frontiersin.org/articles/10.3389/FDMED.2023.1085251/full
16. The Pearl Company; “Can a Computer Identify Carious Lesions in Dental X-Rays as Accurately as Humans?” https://www.hellopearl.com/guides.
17. The Pearl Company; “The Future of Dentistry is Powered by AI;” https://www.hellopearl.com/guides.
18. Weintraub, Pamela; Time Magazine Special Edition; Spring 2024: The Future of Medicine; p. 40-43.
19. Hao Ding, Jiamin Wu, Wuyuan Zhao, Jukka P. Matinlinna, Michael F. Burrow and James K.H. Tsoi (University of Hong Kong); “Artificial Intelligence in Dentistry—A Review;” Frontiers in Dental Medicine; February 20, 2023; p. 5-6.
20. Hao Ding, Jiamin Wu, Wuyuan Zhao, Jukka P. Matinlinna, Michael F. Burrow and James K.H. Tsoi (University of Hong Kong); “Artificial Intelligence in Dentistry—A Review;” Frontiers in Dental Medicine; February 20, 2023; p. 8.
21. Hao Ding, Jiamin Wu, Wuyuan Zhao, Jukka P. Matinlinna, Michael F. Burrow and James K.H. Tsoi (University of Hong Kong); “Artificial Intelligence in Dentistry—A Review;” Frontiers in Dental Medicine; February 20, 2023; p. 6-8.
22. Hao Ding, Jiamin Wu, Wuyuan Zhao, Jukka P. Matinlinna, Michael F. Burrow and James K.H. Tsoi (University of Hong Kong); “Artificial Intelligence in Dentistry—A Review;” Frontiers in Dental Medicine; February 20, 2023; p. 9.
23. Strategy Milling Company in Pittsburgh, PA is at the forefront of milling precious metals. [60 Leetsdale Industrial Drive; Leetsdale, PA 15056; 724-266-3467; www.strategymilling.com]
24. Shah,Simmone (with additional reporting from Linda Marsa); Time Magazine Special Edition; Spring 2024; “How to Make AI Work for You”; p. 39. (updated excerpt from Time, Aug 9, 2023).

About the author

Dr. Feinberg works with dentists who want to improve their crown and bridge skills so that they can deliver better treatment outcomes for their patients. Dr. Feinberg is available to give presentations, and he can put together a presentation at a moment’s notice. Dr. Feinberg’s CV and speaker packet are posted on the website: (https://theonwardproqram.com/about-dr-feinberg/). Dr. Feinberg can be reached at info@theONWARDproqram.com.

AI in laser dentistry: Precision, innovation, and future trends

by admin | Dec 14, 2025 | AIMEDENT Journal

Abstract: The integration of artificial intelligence (AI) and robotics, known as “dentronics,” is transforming laser dentistry through enhanced diagnostic precision, improved patient outcomes, and treatment optimization. AI technologies enable rapid analysis of diagnostic data from imaging systems, facilitating early detection of oral diseases such as caries and oral cancer. When integrated with laser technology, AI can significantly enhance the inherent minimally invasive nature of laser dentistry, further improving precision in tissue ablation and other laser-assisted procedures by leveraging the tissue-selective capabilities of lasers.

Femtosecond laser systems, guided by AI algorithms, demonstrate superior outcomes in hard tissue procedures by minimizing thermal and mechanical damage. Recent innovations in micro/nanorobots and Catalytic Antimicrobial Robots (CARs) have further expanded possibilities for minimally invasive treatments and biofilm eradication. These intelligent robotic systems can navigate the intricate spaces of the oral cavity, delivering targeted therapies and removing pathogenic biofilms with unparalleled accuracy.

Despite these advancements, challenges remain in data privacy, algorithm bias, and regulatory compliance. Safeguarding patient information, ensuring the inclusivity and diversity of training datasets, and establishing clear guidelines for AI-based dental devices are crucial for the responsible implementation of these technologies.

This review explores AI applications across laser-assisted dental procedures, examining current technologies, clinical systems, and emerging trends. It addresses implementation challenges, ethical considerations, and future directions, providing a comprehensive analysis of how AI is reshaping laser dentistry. The integration of these technologies promises to enhance treatment precision, improve patient outcomes, and revolutionize dental care delivery, while necessitating careful consideration of technical, ethical, and practical challenges.

Introduction

1. Fundamentals of AI-enhanced laser dentistry

The integration of artificial intelligence (AI) with laser dentistry represents a fundamental, paradigm shift in dental treatment methodologies and outcomes optimization. This convergence of technologies has created a sophisticated framework that combines advanced machine learning algorithms, high-precision sensing technologies, and intelligent laser control systems to enhance therapeutic efficacy¹.

1.1. Basic principles

The foundational principle underpinning AI-enhanced laser dentistry centers on the system’s capacity to process and analyze vast quantities of clinical data in real-time. Modern AI systems employ sophisticated deep learning algorithms to interpret diagnostic imaging, capable of continuously monitoring tissue response during procedures, that could dynamically optimize laser parameters. This intelligent control system functions as an advanced processing unit that continuously evaluates multiple data streams simultaneously, enabling unprecedented precision in dental procedures².

The AI component’s ability to process real-time feedback from multiple sensors while simultaneously drawing upon extensive databases of previous treatments represents a significant advancement in procedural optimization. This capability enables the system to anticipate and prevent potential complications before they occur and could make a substantial improvement over traditional laser dentistry approaches³.

The technological framework of AI-enhanced laser dentistry comprises several sophisticated components working in concert. Machine learning algorithms form the cognitive core of these systems, utilizing neural networks for complex image analysis and pattern recognition. These algorithms process vast amounts of clinical data to generate predictive models for treatment planning and can provide real-time decision support during procedures⁴.

Advanced sensing systems represent another crucial technological component, which can comprise the incorporation of optical coherence tomography (OCT) integration, real-time temperature monitoring, and tissue response detection. These sensing mechanisms can provide continuous feedback regarding tissue condition and response to treatment, enabling precise control of laser parameters in real-time⁵.

The precision laser control system represents the third key technological element, featuring dynamic power adjustment capabilities, automated focal point optimization, and multi-wavelength synchronization. These advanced control mechanisms can ensure optimal energy delivery while minimizing collateral tissue damage⁶.

1.3. Integration mechanisms

The integration of AI with laser systems occurs through a sophisticated, multi-layered architecture. At its foundation lies a comprehensive data integration platform that synthesizes patient records, real-time procedural data, and diagnostic information into a cohesive dataset. This integration allows the system to develop comprehensive treatment plans based on both historical data and current patient parameters⁷.

Advanced feedback control systems form another crucial integration mechanism, providing continuous monitoring of tissue response and automated adjustment of laser parameters. These systems can incorporate sophisticated safety protocols and emergency stop mechanisms to ensure patient safety throughout the procedure. The integration architecture also includes an intuitive user interface that can enable practitioners to visualize treatment progress in real-time while maintaining precise control over the procedure⁸.

Methods

This comprehensive review was conducted using a systematic approach to literature search and analysis. The search strategy encompassed multiple databases including PubMed, Scopus, Web of Science, and IEEE Xplore, covering publications from 1997 to 2024. Key search terms included combinations of: “artificial intelligence,” “machine learning,” “laser dentistry,” “robotics,” “dentronics,” “micro/nanorobots,” and “AI-enhanced laser systems.”

Selection criteria focused on:

• Peer-reviewed articles in English
• Studies involving AI applications in laser dentistry and general dentistry
• State-of-the-art reviews on AI in dental applications
• Technical reports on AI-laser integration and robotics in dentistry
• Original research on AI applications in dental diagnosis and treatment

Articles were evaluated for relevance and significance of findings. Priority was given to:

• Recent publications (2019-2024) for current AI applications and trends
• Foundational studies in AI-enhanced dental systems
• Innovative developments in AI, robotics, and laser integration
• Key papers on femtosecond lasers and tissue interactions
• Commercial AI dental applications and systems

The literature review process involved:

1. Initial screening of titles and abstracts for relevance to AI in dentistry
2. Full-text review of selected articles
3. Analysis of AI applications and technological developments
4. Synthesis of findings across different dental specialties
5. Identification of current trends and future directions in AI-enhanced laser dentistry

2. AI-enhanced applications in clinical practice

The implementation of AI-enhanced laser dentistry can span a broad spectrum of clinical applications, from diagnostic procedures to post-treatment monitoring. The integration of these technologies can significantly enhance the precision and efficacy of dental treatments across multiple specialties.

2.1. Diagnostic applications

AI-powered diagnostic capabilities have revolutionized the detection and assessment of oral pathologies. Advanced imaging analysis systems, particularly when integrated with laser-based diagnostic tools, demonstrate remarkable accuracy in identifying early-stage dental conditions. For instance, AI algorithms can process imaging data from laser fluorescence devices and optical coherence tomography (OCT) to detect early signs of caries and periodontal disease with unprecedented precision⁵.

In periodontics, AI systems excel at analyzing clinical attachment levels, probing depths, and bone loss patterns through radiographic interpretation. These systems can integrate multiple data points to predict disease progression and treatment outcomes with high accuracy⁹. Technology has proven particularly valuable in detecting subtle changes that might be overlooked during conventional examination. Integrated with laser technology it can amplify treatment capabilities and enhance prognostic.

2.2. Treatment planning

AI-driven treatment planning represents a significant advancement in personalized dental care, leveraging patient-specific data, including medical history, diagnostic imaging, and previous treatment outcomes, to generate comprehensive treatment protocols. These AI algorithms can simulate various treatment scenarios and predict their outcomes, allowing clinicians to select the most appropriate approach for each patient¹⁰. Furthermore, AI-powered Clinical Decision Support Systems (CDSS) are transforming treatment planning by integrating patient data with evidence-based guidelines to offer personalized, data-driven treatment recommendations. These systems analyze factors such as medical history, dental images, lifestyle, medication interactions, allergies, and contraindications, ensuring each patient receives the most effective and safe care protocol⁸.

2.3. Clinical procedures

2.3.1. AI across dental specialties

AI technologies are increasingly applied across various dental specialties to enhance diagnostic accuracy, treatment planning, and precision. In operative dentistry, AI assists in detecting caries, fractures, and other pathologies through deep learning on radiographic images^11,12. In orthodontics, AI aids in treatment planning and simulating facial alterations^13,14. AI is also transforming implantology by improving surgical precision and treatment outcomes through CBCT analysis, robotic assistance, and AI-guided navigation^15,16. In prosthodontics, AI helps optimize prosthetic design and occlusion^10,17. AI also contributes to 3D digital dentistry by enhancing CAD/CAM workflows¹⁸. Additionally, AI supports bioprinting technologies for reconstructing oral tissues^19,20.

2.3.2. AI in laser dentistry

The integration of AI in laser-assisted dental procedures has the capability to significantly enhance precision and predictability. In restorative dentistry, AI-guided laser systems could offer superior accuracy in cavity preparation and caries removal by continuously monitoring tissue responses and automatically adjusting laser parameters to optimize cutting efficiency while preserving healthy tissue²¹. The ideal AI systems should be capable of further optimizing laser treatment parameters by analyzing tissue characteristics and patient-specific factors, enabling precise calibration of laser power, pulse duration, and focal point positioning. This would ensure maximum therapeutic effectiveness while minimizing collateral tissue damage. Periodontal treatment can benefit significantly from Laser-AI integration, where technology enables precise removal of calculus and diseased tissue while preserving healthy structures. AI-guided systems could differentiate between various tissue types in real-time, ensuring targeted treatment delivery²².

2.3.3. Post-treatment monitoring

AI systems have transformed post-treatment monitoring through automated assessment of healing progression and treatment outcomes. These systems can analyze follow-up imaging and clinical measurements to evaluate treatment success and identify potential complications early. The technology enables continuous monitoring of tissue response and healing patterns, allowing for timely intervention if needed⁶. Furthermore, AI algorithms can predict long-term treatment outcomes based on early healing indicators and patient-specific factors. This predictive capability allows clinicians to modify post-treatment protocols proactively, optimizing healing outcomes and patient satisfaction²³.

3. Advanced technologies and innovations

AI’s role in healthcare extends beyond diagnostics and treatment planning, finding applications in robotic systems, diagnostic tools, and drug discovery, further contributing to advancements in dental care⁶. The convergence of AI with advanced laser technologies has catalyzed significant innovations in dental treatment methodologies. These developments represent a fundamental shift toward more precise, minimally invasive, and intelligent therapeutic approaches.

3.1. Femtosecond lasers

Femtosecond laser technology, when integrated with AI systems, represents a significant advancement in hard tissue ablation. Traditional methods, including mechanical drilling and conventional laser systems, often generate mechanical and thermal stress, potentially causing micro-cracks in dental enamel measuring several tens of microns. In contrast, femtosecond lasers guided by AI can achieve precise tissue ablation without inducing structural damage²¹.

Research has demonstrated that femtosecond laser ablation can create cavities in dental tissue without inducing cracks, while offering selective control over refractive index changes²⁴. This technology enables the preferential removal of specific portions of dental hard tissues, demonstrating unprecedented precision in tissue manipulation²⁵.

3.2. AI-guided laser systems

A notable innovation in this field is the development of AI-driven feedback systems that incorporate multiple sensing modalities⁴. These senses have the potential to continuously monitor parameters such as tissue temperature, ablation depth, and surrounding tissue status, enabling precise control over the laser-tissue interaction. Furthermore, advanced AI-guided systems can incorporate sophisticated algorithms that enable real-time analysis of tissue response to make automatic adjustment of laser parameters which utilize machine learning models trained on extensive datasets⁷. This capability could optimize energy delivery patterns for different dental procedures. The integration of AI into laser devices could enable dynamic adaptation to individual patient characteristics and specific tissue responses during treatment.

3.3. Robotics integration

The emergence of “dentronics” – the fusion of robotics and AI in dentistry – addresses the global shortage of skilled dental professionals while enhancing treatment precision⁶.

The integration of robotics with AI-guided laser systems has led to the development of sophisticated platforms such as the “LaserBot,” which achieves high-resolution 3D manipulation within the confined space of the oral cavity. These robotic systems utilize advanced motion control mechanisms, including voice-coil motors and parallel five-linkage systems, demonstrating average repeatability errors as low as 40 μm⁷.

3.4. Micro/nanorobots and CARs

A revolutionary advancement in the field is the development of Catalytic Antimicrobial Robots (CARs), which leverage iron oxide nanoparticles with dual catalytic-magnetic functionality. These sophisticated systems execute a three-fold strategy: generating bactericidal free radicals, degrading the biofilm’s exopolysaccharide matrix, and removing fragmented debris through magnetic field manipulation²⁶.

The integration of AI with micro/nanorobots has revolutionized precision navigation in complex biological environments, enabling targeted drug delivery and minimally invasive procedures. These systems excel at accessing previously unreachable areas of the oral cavity, opening up new possibilities for treating a variety of dental conditions²⁷. This advancement aligns well with laser dentistry, as laser beams can reach areas of the oral cavity that are inaccessible to traditional mechanical instruments. Together, these technologies can enhance the prognosis of periodontally compromised teeth by improving precision in treatment delivery and reducing invasiveness.

4. Current commercial solutions and clinical applications in dentistry

The practical implementation of AI in dental practice is exemplified by several commercially available systems that demonstrate the current state of technology. These systems can be categorized by their primary functions and clinical applications:

4.1. Diagnostic and imaging analysis systems: Overjet®²⁸ is an AI-powered diagnostic tool currently available in clinical practice. Pearl’s Second Opinion®²⁹ provides real-time analysis of radiographs, detecting conditions such as cavities, calculus, and periapical radiolucency. Similarly, it offers comprehensive analysis of dental X-rays, automating the identification of common conditions while integrating with existing practice management systems.

4.2. Clinical Decision Support Systems: Advanced AI-powered Clinical Decision Support Systems (CDSS) enhance treatment planning and clinical decision-making. Notable examples include Denti.AI®³⁰, which automates dental image interpretation and pathology identification, and Carestream Dental’s Logicon Caries Detector®³¹, an FDA-approved system specifically designed for interproximal caries detection⁸.

4.3. Remote monitoring and patient management: DentalMonitoring®³² exemplifies the integration of AI in patient care management, enabling remote monitoring of orthodontic and dental patients through smartphone-based imaging analysis. This system allows for treatment plan adjustments without requiring in-person visits, representing a significant advancement in teledentistry applications.

4.4. Practice management and documentation: Systems like Athelas AI Scribe®³³ and Dentrix®³⁴ by Henry Schein demonstrate the practical application of AI in clinical documentation and practice management. These platforms automate administrative tasks, improve documentation accuracy, and integrate with diagnostic tools to provide comprehensive patient care management.

The implementation of these systems in clinical practice has demonstrated tangible benefits in several key areas:

• Enhanced diagnostic accuracy through AI-powered image analysis
• Improved treatment planning through data-driven decision support
• Increased practice efficiency through automated documentation and workflow optimization
• Enhanced patient engagement through remote monitoring capabilities

5. Implementation and integration framework

5.1. Strategic implementation: The successful implementation of AI-enhanced laser dentistry requires a coordinated approach involving clinical practitioners, academic institutions, regulatory bodies, and industry partners. This multi-stakeholder framework addresses both practical implementation challenges and long-term integration requirements.

Implementation at the clinical level demands significant adaptation of existing workflows and substantial investment in infrastructure. Physical space constraints in dental offices necessitate careful planning for equipment installation, while integration with existing practice management software and imaging systems requires sophisticated technical solutions⁶.

5.2. Multi-stakeholder collaboration: The advancement of AI-enhanced laser dentistry relies heavily on synergistic relationships between stakeholders. Clinical experiences inform technical refinements, while industry innovations enable new therapeutic possibilities. For example, the development of the “LaserBot” system emerged from direct collaboration between clinicians identifying precise manipulation needs and engineers developing miniaturized robotic solutions⁷.

Industry stakeholders face parallel challenges in developing solutions that meet clinical needs while ensuring commercial viability. The substantial investment required for research and development must balance market acceptance and regulatory compliance. Manufacturers must provide comprehensive support infrastructure while managing development timelines and production costs.

5.3. Data and technology integration: The effectiveness of AI algorithms depends on the quality and quantity of clinical data available for training. Industry partners provide technical infrastructure for data collection and analysis, while clinicians contribute valuable real-world treatment outcomes and patient responses. This symbiotic relationship has led to improvements in treatment protocols and system optimization, as evidenced by the evolution of automated parameter adjustment systems⁴.

Data security and privacy considerations present significant challenges. As AI systems collect and process increasing amounts of patient data, ensuring compliance with regulations such as HIPAA (Health Insurance Portability and Accountability Act, the U.S. healthcare privacy law) and GDPR (General Data Protection Regulation – the European Union’s privacy regulation) becomes crucial. This necessitates careful attention to data management protocols and security measures at both clinical and industry levels³⁵.The need to balance data accessibility for AI system improvement with patient privacy protection remains a significant concern.

5.4. Education and training initiatives: Joint efforts between clinical institutions and manufacturers are essential for successful technology adoption. Industry-sponsored training programs, combined with clinical expertise, create comprehensive education systems addressing both technical proficiency and clinical application. The integration of VR/AR training platforms with real-world clinical scenarios exemplifies this collaborative approach to professional development¹.

Regular calibration, maintenance, and quality assurance protocols ensure optimal system performance and reliability. Documentation and systematic assessment help optimize clinical protocols and identify areas for improvement, leading to standardized procedures and certification processes that maintain high clinical standards.

5.5. Regulatory framework and standards development: The establishment of safety standards and clinical protocols requires coordinated effort between practitioners, manufacturers, and regulatory bodies. Clinical experience informs regulatory requirements, while industry expertise ensures technical feasibility. This collaboration has been particularly crucial in developing guidelines for AI-enhanced laser parameters and safety protocols³⁶.

The regulatory landscape for AI in healthcare continues to evolve, presenting challenges for technology adoption. Current frameworks from organizations such as ISO (International Organization for Standardization), FDA (U.S. Food and Drug Administration), and European regulatory bodies may not fully address the unique characteristics of AI-enhanced dental devices, particularly those that continue to learn and adapt through use³⁷.

5.6. Ethical concerns: Ethical considerations encompass several critical areas, with algorithm bias representing a significant concern. AI systems trained on non-representative datasets may perpetuate or amplify existing healthcare disparities³⁸. Questions of accountability and responsibility in AI-assisted procedures require careful consideration, particularly regarding liability in cases where AI systems contribute to adverse outcomes¹.

The high costs associated with implementing AI-enhanced laser systems may create disparities in access to advanced dental care, raising ethical concerns about healthcare equity³⁹.

Maintaining appropriate human oversight and ensuring that AI systems remain tools to augment rather than replace clinical judgment presents ongoing ethical considerations.

5.7. Strategic analysis of AI-driven laser dentistry

A structured analysis known as SWOT (Strengths, Weaknesses, Opportunities, and Threats) provides a systematic framework for evaluating AI integration in laser dentistry, as illustrated by Tables 1 & 2. This strategic planning tool identifies internal factors (strengths and weaknesses) and external factors (opportunities and threats) that can impact the successful implementation of AI-enhanced laser dentistry from both clinical and manufacturing perspectives. The analysis provides a comprehensive evaluation of the current state and future potential from dual viewpoints: clinical implementation and industry development. Additional Clinical Strengths of AI-Driven Lasers include:

• Improved tissue healing monitoring
• Enhanced treatment predictability
• Better infection control through AI-guided systems
• More precise pain management
• Improved long-term outcome tracking
• Better integration of multiple treatment modalities
• Enhanced quality control measures
• Standardized treatment protocols

Table 1: SWOT Analysis – Clinical implementation perspective

Table 2: SWOT Analysis – Industry and market perspective

Discussion

6. Clinical impact and implementation

The integration of artificial intelligence with laser dentistry represents a transformative advancement in dental care, offering unprecedented precision, enhanced diagnostic capabilities, and optimized treatment outcomes. This review has identified several key patterns and implications for clinical practice.

6.1. Current state and clinical impact

The convergence of AI and laser technologies has demonstrated significant improvements in treatment precision and patient outcomes. AI-guided laser systems have shown particular promise in three critical areas: diagnostic accuracy, treatment customization, and real-time procedural optimization. The ability to process multiple data streams simultaneously while adjusting laser parameters has enabled a level of precision previously unattainable with conventional approaches. Early clinical evidence suggests potential for reduced collateral tissue damage and improved healing outcomes, particularly in procedures requiring precise tissue discrimination such as periodontal surgery and caries removal.

7. Technology integration and challenges

7.1. Implementation considerations

While the potential benefits are substantial, successful implementation of AI-enhanced laser systems requires careful consideration of several factors. The initial investment in both equipment and training represents a significant barrier for many practices. However, cost-benefit analyses suggest potential long-term advantages through improved treatment efficiency and outcomes. The learning curve for dental professionals varies significantly, with evidence indicating that structured training programs and gradual integration of AI features lead to more successful adoption.

7.2. Technical integration and safety

The integration of AI with existing dental laser systems presents both opportunities and challenges. Current evidence demonstrates that AI can enhance safety through real-time monitoring and automated parameter adjustment, potentially reducing the risk of operator error. However, the reliability of these systems depends heavily on the quality of their training data and the robustness of their algorithms. This underscores the importance of ongoing validation studies and regulatory oversight to ensure consistent performance and patient safety.

8. Future directions, research needs, and clinical implications

AI-enhanced laser dentistry is poised for significant growth, offering promising improvements in precision and patient outcomes. However, long-term clinical studies are essential to validate the durability of AI-augmented laser treatments compared to traditional methods. Standardizing AI algorithms across different laser platforms is another critical step for the industry. Moreover, the miniaturization of femtosecond laser systems integrated with AI will expand applications in confined oral spaces, making treatments more versatile^7,21,25.

8.1. Clinical practice implications

AI-driven systems, while not replacing clinical judgment, augment decision-making and improve procedural precision, facilitating a transition from experimental to practical clinical tools. The integration of Catalytic Antimicrobial Robots (CARs) and micro/nanorobots with AI-guided lasers presents promising opportunities for minimally invasive treatments, enhancing biofilm management and localized therapeutic delivery²⁶.

This ongoing evolution in dental care requires updated clinical protocols and training methodologies, with a focus on balancing innovation with clinical validation to ensure optimal patient care. AI-enhanced lasers could improve precision in hard-to-reach areas, leading to better outcomes in periodontally compromised teeth.

8.2. Future perspectives

The evolution of AI in laser dentistry suggests several key developments that will shape clinical practice. In the near term (1–3 years), the focus will be on enhanced integration of AI systems with existing laser platforms. This includes real-time data processing, improved tissue response monitoring, and optimized laser parameters for more personalized treatments. Clinical workflow optimization is also expected, including automated documentation and predictive maintenance of laser systems, which will streamline practice management¹.

In the medium term (3–5 years), AI-guided robotics will integrate more fully with laser systems, featuring miniaturized delivery systems for confined oral spaces, advanced haptic feedback, and navigation systems for complex procedures. Continued development of micro/nanorobots will enhance targeted drug delivery and precision tissue manipulation, expanding the scope of minimally invasive procedures^26,27.

Longer-term (5+ years) breakthroughs may include quantum computing for complex treatment planning, self-learning AI systems for continuous improvement, and advanced biomimetic materials responsive to laser treatments. These advancements will require the development of standardized protocols, enhanced safety guidelines, and updated clinical best practices, ensuring AI’s responsible and safe integration into routine care^36.37.

As AI-guided laser dentistry moves forward, successful implementation will depend on continued research and collaboration among clinicians, regulatory bodies, and industry partners. Balancing technological innovation with clinical validation is crucial to ensuring these advances translate into safe, effective, and accessible patient care in the future.

Conclusion

AI is transforming laser dentistry, offering unprecedented precision, enhanced diagnostic capabilities, and optimized treatment planning. The integration of AI with laser devices enables real-time feedback, personalized treatments, and predictive analytics, revolutionizing procedural approaches and outcomes. Key innovations such as AI-guided laser systems, robotic laser devices, and micro/nanorobotic technologies, including Catalytic Antimicrobial Robots (CARs) for biofilm eradication, can reshape both preventive and restorative laser procedures.

However, the implementation of AI-enhanced laser systems faces significant challenges. Data privacy concerns, algorithmic bias, and the need for robust regulatory frameworks remain barriers to wider adoption. The high cost of these advanced systems and the steep learning curve for practitioner’s limit accessibility, particularly in smaller practices.

Despite these hurdles, the future of AI in laser dentistry holds immense potential. The continuous evolution of AI technologies, particularly in conjunction with robotic laser systems, augmented reality (AR), and virtual reality (VR), offers exciting opportunities for more precise, minimally invasive treatments and enhanced clinical training. Ongoing advancements in AI algorithms and laser-sensing technologies promise even greater levels of safety, efficiency, and effectiveness in dental procedures.

As the field progresses, collaboration between dental practitioners, researchers, and regulators will be essential to harness the full potential of AI-enhanced laser dentistry while addressing ethical, technical, and safety concerns. The future appears bright, promising to transform both the quality of laser-based dental care and the accessibility of advanced treatments globally.

Glossary of AI Terms in laser dentistry

Artificial intelligence (AI): Computer systems designed to perform tasks that typically require human intelligence. In dentistry, AI helps analyze images, make diagnostic suggestions, and optimize treatment planning. Unlike standard computer programs, AI systems can learn from experience and adapt their responses.

Machine learning (ML): A subset of AI that enables computer systems to improve their performance through exposure to data without explicit programming. In dental applications, ML algorithms can learn to recognize patterns in radiographs or predict treatment outcomes based on patient data.

Deep learning (DL): An advanced form of machine learning using multiple layers of neural networks to analyze complex patterns. In dental imaging, deep learning can identify subtle features in radiographs that might be missed by human observation.

Neural networks: Computing systems inspired by human brain structure, consisting of interconnected nodes that process information. In dental applications, neural networks can analyze multiple data points simultaneously to assist in diagnosis and treatment planning.

Computer vision: AI technology that enables computers to understand and process visual information from the world. In dentistry, computer vision analyzes radiographs, intraoral photos, and scan data to assist in diagnosis and treatment planning.

Clinical AI applications

Clinical Decision Support Systems (CDSS): AI-powered software tools that assist dental professionals in making clinical decisions by analyzing patient data, imaging results, and treatment histories to provide evidence-based recommendations.

Predictive analytics: The use of AI to analyze current and historical data to make predictions about future outcomes. In dentistry, this can help forecast treatment success rates or identify patients at risk for specific conditions.

AI risk of bias: The potential for AI systems to produce unfair or skewed results due to limitations or imbalances in their training data. Understanding this concept is crucial for ensuring equitable patient care.

Real-time processing: The ability of AI systems to analyze and respond to information as it is received. In laser dentistry, this enables immediate adjustments to laser parameters based on tissue response.

Integration technologies

Dentronics: The integration of robotics and AI in dental procedures, combining precise mechanical control with intelligent decision-making capabilities.

Augmented reality (AR): Technology that overlays digital information onto the real world. In dental procedures, AR can provide real-time guidance during laser treatments by displaying important anatomical landmarks or treatment targets.

Virtual reality (VR): Immersive computer-generated environments used for training and treatment planning in dentistry.

Mixed reality: A combination of real and virtual environments where physical and digital objects interact in real-time, useful for treatment planning and surgical guidance.

Robotics and laser systems

Microrobots/Nanorobots: Microscopic robotic devices that can perform precise tasks within the oral cavity. When integrated with AI, they can navigate autonomously and provide real-time feedback during procedures.

Catalytic Antimicrobial Robots (CARs): Advanced microscopic devices that combine AI guidance with antimicrobial capabilities to target and eliminate bacterial biofilms in hard-to-reach areas.

AI-enhanced laser parameters: The automated adjustment of laser settings (power, pulse duration, focal point) based on real-time tissue feedback and AI analysis.

Dynamic power adjustment: Automated modification of laser power output based on AI analysis of tissue response and treatment goals.

Advanced integration features

Automated focal point optimization: AI-driven adjustment of laser focus to maintain optimal tissue interaction throughout procedures.

Multi-wavelength synchronization: AI-controlled coordination of different laser wavelengths to achieve optimal therapeutic effects.

Tissue response monitoring: Real-time AI analysis of tissue changes during laser procedures to optimize treatment parameters and prevent damage.

Real-time tissue classification: AI-powered identification and categorization of different tissue types during procedures to ensure appropriate laser settings.

Data management

Automated data mining: AI-driven analysis of large datasets to identify patterns and trends in treatment outcomes, patient responses, and clinical efficacy.

Pattern recognition: AI capability to identify meaningful patterns in clinical data, imaging results, and treatment responses.

Biofeedback systems: Integration of biological sensors with AI analysis to provide real-time information about tissue response during laser procedures.

Haptic feedback refers to the use of tactile sensations, such as vibrations or physical resistance, to communicate information to a user. In the context of medical and dental robotics, haptic feedback provides real-time physical cues to the operator, enabling them to feel resistance or pressure during procedures. This sensory input helps improve precision and control, especially in delicate or complex tasks like surgery, by simulating the sensation of touching or manipulating tissues. It enhances the operator’s ability to perform minimally invasive procedures with greater accuracy and safety.

SWOT Analysis: A strategic planning and evaluation framework that examines four key factors:

• Strengths: Internal attributes and resources that support successful implementation
• Weaknesses: Internal limitations and challenges that may hinder success
• Opportunities: External factors and trends that could be beneficial
• Threats: External elements and conditions that could cause problems

Regulatory terms:

• HIPAA (Health Insurance Portability and Accountability Act): A 1996 U.S. federal law that created national standards to protect sensitive patient health information from being disclosed without the patient’s consent or knowledge.
• GDPR (General Data Protection Regulation): A comprehensive data protection law implemented by the European Union in 2018 that sets strict standards for the collection, storage, and use of personal information, including healthcare data.

Regulatory frameworks and organizations related to product safety and quality:

ISO (International Organization for Standardization): ISO is an independent, non-governmental international organization that develops voluntary, consensus-based international standards related to product safety and quality.

FDA (U.S. Food and Drug Administration): The FDA is a federal agency responsible for protecting public health in the United States. Its regulations cover areas like product testing, labeling, manufacturing, and post-market surveillance to ensure the safety and efficacy of regulated products.

Financial support: The author has not received financial support.

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About the author

Dr. Sonia Bordin-Aykroyd, President of the Dental AI Association South America and Chair of the Division of Laser Dentistry, is an expert in minimally invasive dental and facial esthetics. She runs two academies in Dallas, practices cranio-facial sleep medicine in Brazil, and is a front-runner in dental laser technology.

The AI-enhanced “Perfect Smile Retainer”

by admin | Dec 14, 2025 | AIMEDENT Journal

Artificial intelligence is like a divine power that can turn dust into gold. The progress in machine learning and artificial intelligence is revolutionizing all aspects of human life. It streamlines tasks, saves time, reduces costs, and frees humans from the hassle of tiring activities. Many believe that the advent of AI programs is the next big invention after the creation of the wheel. The corporate sector is aptly utilizing the benefits offered by AI, but the good thing is that its application is not limited to big business firms and computer-people.

Fortunately, AI stands at the forefront of the continuously evolving medical landscape. For decades, healthcare professionals have strived to improve clinical efficiency, reduce health burden, and enhance prognosis. However, with AI in the picture, doctors from across the globe have reported significant improvements in clinical efficiency, patient management, and treatment results. Reports suggest that the healthcare AI market is expected to reach above $188 billion by 2030.

How AI is revolutionizing orthodontics and dentistry

AI programs are based on machine learning (ML) algorithms that use pattern recognition. These highly advanced algorithms identify patterns in the provided data and can differentiate between normalcy and abnormalities based on these patterns. ML finds applications in numerous healthcare fields including radiology, genetics, neuroimaging, etc. Complex forms of machine learning are neural networks and deep learning algorithms.

In deep learning, the program analyzes the provided data more deeply than the human eye. This allows AI to pick up details that a human may miss. Paired with the deep learning model is a neural network (a learning model) that mimics the human brain in decision-making. These programs undergo unsupervised learning, so they learn from the patterns present in the provided data pool. This makes them free of bias and decision noise.

Multiple aspects of dental treatment are augmented with the incorporation of healthcare AI. Orthodontists have reported considerable improvements in the following facets of orthodontic treatment:

Diagnosis

Diagnosing malocclusion is a laborious task as it involves going through radiographs, patient records, and clinical pictures. An in-depth analysis of a patient’s condition requires the orthodontist to identify landmarks on cephalometric x-rays, determine the skeletal age of the patient (using cervical vertebrae maturation stage i.e., CVM), and diagnose maxillomandibular relationships. The process of reaching an accurate diagnosis requires the extensive skills of the healthcare provider. Moreover, it takes a lot of time and effort.

But with AI, there is an astonishing improvement in the working procedures. It takes the burden off of the dentist in multiple ways. AI programs like YOLOv3 (You Only Look Once Version 3) can accurately identify as many as 80 cephalometric landmarks (that too in a matter of seconds!). In a study comparing human subjects and AI algorithms, the automated system repeatedly excelled against the human competitor. The AI-based diagnostic analysis had faster speeds, less variability, and minimal detection error. It also allows you to delve into a broader landscape of orthodontics by giving a diagnosis based on the complete facial profile (instead of the conventional jaw relations).

As per a 2024 study, the brilliance in diagnostic capabilities of AI is attributed to the continuous iterations in AI systems. The incorporation of artificial intelligence algorithms allows enhanced visualization of outcomes and precise diagnoses.

Treatment planning

As AI algorithms offer reliable and quick diagnoses, doctors can rely on the treatment plans offered by the automated system. A keen eye for radiographic images, facial profiles, and extensive machine learning training enables the AI software to provide workable solutions for orthodontic problems. According to studies, high-quality artificial neural networks (ANNs) can help provide the right diagnosis to even inexperienced orthodontists.

Extracting or going for interproximal reduction (IPR) is a key question in orthodontics. When dealing with humans, every case is different and even the most experienced orthodontists can get stuck in decision-making. AI can make life easier yet again!

The latest clinical studies reveal that automated systems perform “exceptionally well” and have shown accuracy and precision similar to trained professionals. The advanced algorithms can guide you regarding the required type of orthodontic treatment, and/or the need for orthognathic surgery.

Appliance manufacturing

Another commendable feature of artificial intelligence used in routine orthodontic practice is the manufacturing of highly precise and effective orthodontic appliances. Additive manufacturing (or 3D printing) is an advanced industrial process that develops precise geometric 3D appliances/devices.

The collaboration of AI software and innovative hardware allows orthodontists to create orthodontic appliances (such as aligners, orthopedic appliances, and retainers) that are more precise and reliable than conventional methods. A 2023 study concluded that orthodontic retainers built via 3D printing had the following benefits:

• Time and cost-efficient
• More comfortable to wear
• Solve esthetic problems
• Retainer materials do not interfere with Magnetic Resonance Imaging (MRI)
• Help resolve periodontal issues

Creating the “Perfect Smile Retainer”: Amalgamating technology with innovation

Artificial intelligence also enables you to think out of the box. With smart AI applications and professional bravura, orthodontists can visit unexplored territories. One such innovation resulting from AI incorporation is the “Perfect Smile Retainer” aka PSR.

The PSR is a unique, and multi-purpose product that has multiple therapeutic advantages (which we will discuss later!). The perfect smile retainer is a modified type of orthodontic retainer that additionally acts as a smile enhancer. There are plenty of reasons to love the perfect smile retainer but first, let’s know about an orthodontic retainer.

What is an orthodontic retainer?

An orthodontic retainer is a custom-made device given to an orthodontic patient after the completion of the treatment. The main aim of a retainer is to keep the straightened teeth in their new position and to prevent relapse. There are different types of retainers including:

Hawley retainers: These are removable retainers and are made out of a metal wire and acrylic plate.

Clear plastic retainers: Common types of modern clear aligners include Essix, Zendura, and Vivera retainers. Such types of retainers have a transparent look and are made out of plastic/polyurethane.

Fixed retainers: These are permanently bonded/fixed to the teeth. Bonded retainers are usually made out of metal wires (nickel-titanium or copper, etc.).

Perfect Smile Design Retainer: A remarkable modification

The PSR is a modified form of a clear plastic retainer that provides aesthetic enhancements to your smile. The PSR has a palatal extension for support and retention that aptly holds the orthodontically corrected teeth in place.

The facade (front-facing side) of the retainer can be modified according to the patient’s needs. So, if someone isn’t satisfied with the shape, color, or size of his/her teeth and doesn’t want to spend hefty amounts on cosmetic dental treatment can opt for this potent appliance. All such patients can enjoy a pleasant smile with the help of the “perfect smile” design. Some evident and unique features of the smile design include:

• The appliance is flexible and very easy to use. As it is custom-made for each patient, the retainer device snaps onto your teeth without any trouble or hassle.
• Facade modifications allow the patient to choose between transparent/clear appliances or the addition of whiter tooth shade to make their teeth look ultra-white.
• It ensures the ideal finishing of orthodontic cases. As the appliance is developed using the Golden Proportions SmarTooth app, the retainer can serve as a check for Bolton’s discrepancies in finished cases.
• Unlike the prevalent orthodontic retainer, the PSR is worn during the daytime and left out during the night (sleep time). This feature is attributed to the esthetic enhancement effects of the appliance.

Who can benefit from a Perfect Smile Retainer?

• Orthodontic patients who have completed treatment and need retainers.
• Patients who want to enhance their smile while they are in retention. This includes anyone unsatisfied with the shape and size of the teeth (after completion of treatment).
• People with crooked teeth, who are looking for an affordable smile makeover until they plan for more permanent teeth straightening and reshaping therapies.
• Individuals who are unsatisfied with the shape and color/shade of their teeth and want a more affordable provisional solution.

The amazing iPhone SmarTooth app

Expert orthodontists developed the multi-purpose smile analysis tool i.e., the “Perfect Smile Design” by using advanced AI-based programming.

One such application is the SmarTooth iPhone Application developed by the Medical College of Georgia Orthodontic Department. It is a great app that helps dentists (orthodontists, cosmetic dentists, etc.) get an idea of the ideal width and height of teeth and points out any anatomical discrepancies. Furthermore, the application can be used to get analyses like Moyers and Tanaka-Jhonston’s analyses, Bolton’s size discrepancies, and smile analysis. All you have to do is insert one tooth measurement (upper or lower) and the smart algorithm measures and provides you with the ideal widths/heights of all the teeth.

You can download this amazing free app from the Apple App Store by clicking here!

EXOCAD App: A game changer

The EXOCAD app owned by the Invisalign Company is another application that is required for the development of the Perfect Smile Retainer. It is computer-aided design software used by dental specialists across the globe. The apps have different modules that allow dentists to get perfect 3D (digital) scans (intra-oral and facial). This app has proven to be a significant factor in the development of the perfect smile-designed retainer. EXOCAD has revolutionized the world of digital dental diagnostics.

Doctors can learn how to use the software by following the tutorials. You can get the EXOCAD app by clicking here!

Benefits of a Perfect Smile Retainer using AI designs

The amalgamation of a retainer with a smile enhancer has so many benefits that it will blow your mind. So, get ready to be impressed with the Perfect Smile Retainer:

Exceptional aesthetics

The one feature that benefits wearers is the exceptional aesthetics offered by the PSR unique orthodontic retention device. Patients seeking revamping of their smiles are ecstatic with the results. The specially designed retainer is developed using the SmarTooth app which gives esthetic solutions based on the golden proportions.

Great minds of ancient times identified specific patterns in the creation of Mother Nature. Therefore, they concluded that the universe follows certain rules and proportions to be in its best form. Leonardo da Vinci, a famous artist and engineer drew the ideal man by considering the golden proportions of the body (including the teeth). The golden proportions include the specific width, length, and height of the teeth. These proportions are still considered the gold standard in the field of esthetic dentistry.

The Perfect Smile Retainer helps patients emulate the golden standards for beauty. Thus, exceptional smile esthetics are guaranteed with this innovative orthodontic retainer!

Boosts confidence

Your perception of yourself plays an integral role in determining the level of your self-confidence. Researchers have found that smile type and wrongly positioned teeth are directly associated with low confidence in smiling. It was found in a study that both males and females preferred having the whitest shades of teeth to get optimal self-confidence levels.

The perfect smile retainer not only covers tooth size discrepancies but also allows you to get a whiter shade of the teeth by custom modifications of the facade. Therefore, retainer wearers report significant boosts in confidence. The raised self-confidence is linked to betterment in different aspects of life. Research suggests that individuals with high self-confidence and self-ability have better employee performance. Thus, by wearing the perfect smile, you can feel internally motivated which may help you land that dream job!

Moreover, an attractive smile profile can also aid in getting the best boyfriend/girlfriend/partner. The famous proverb goes “beauty lies in the eyes of the beholder”. However, you can alter the beholder’s perception by shining your radiant perfect teeth into his/her sight. An ideal smile is sure to attract many new friends!

Ideal results

In addition to embellishing your facial features, the perfect retainer serves a more functional purpose. When given to finished orthodontic cases, it ensures there are no anatomical disparities. The palatal extension ensures solid support and retention. This keeps the corrected teeth in position and the AI Smile Design eliminates Bolton discrepancies (i.e., one side of the mouth may have wider or smaller tooth dimensions than the other).

Comfort and ease of use

The perfect retainer does not require you to undergo extensive dental work (bridges, veneers, comprehensive orthodontic treatments) to achieve the perfect smile you’ve always wanted. It is a hassle-free appliance that tightly fits on your teeth and lets you wear your ideal smile. Patients report that wearing the PSR is easy, and they love how it firmly snaps onto their teeth without the need for dental cementation.

Better patient compliance

The PSR is designed to allow better patient compliance. Contrary to today’s common retainers, this retainer is worn during the day and left out at night. This allows patients to have better, uninterrupted sleep. It also amplifies facial aesthetics and patients are inclined towards wearing it throughout the day (when interacting with people). Thus, this unique type of retainer has better patient compliance potential than its counterparts.

How is the Perfect Smile Retainer developed?

Here we discuss a clinical case treated with the Perfect Smile Retainer appliance by myself, Dr. Paul Ouellette. The patient was treated for spacing in teeth with adjunctive orthodontic treatment with fixed braces and retained by the Perfect Smile Retainer.

Application use

The start of the treatment plan relies on the use of two well-developed applications, i.e., EXOCAD and the iPhone App SmarTooth.

Conclusion

The combined use of professional craftsmanship and automated intelligence leads to the creation of unique and effective things. The implementation of AI in healthcare has led to significant improvements. Similarly, AI orthodontics has enhanced clinical efficiency and sped up the process of diagnosis. Moreover, AI and machine learning algorithms provide persistent and reliable treatment options for orthodontic problems.

The PSR is a multi-purpose appliance that also can be used as a provisional trial smile device before orthodontics or cosmetic dentistry. It is designed with the latest technology, i.e., digital impressions using the EXOCAD app and smile proportions with the smarTooth app with 3D printing. Certain features set the PSR apart. It has a palatal extension that offers robust support and prevents relapse after orthodontic correction. The modification of the trial smile facade allows patients to use the retainer as a smile enhancer (adjusts teeth width and height according to the DaVinci golden proportions). It also allows the patient to alter the color of their teeth. Unlike conventional appliances, the Perfect Smile Retainer is worn during the day and left out during the night.

Numerous clinical studies show that patients with an AI-enhanced smile are more employable, desirable, and more quickly accepted into society. Patients with the Perfect Smile Retainer have boosted self-esteem and confidence and are highly likely to land a higher-paying job. Getting accepted in society and being attracted to the opposite gender is also relatively easy. The appliance easily snaps into place and has greater acceptability. Thus, the retainer has better patient compliance and is undoubtedly an exceptional innovation in the field of dentistry.

References

1. https://www.statista.com/statistics/1334826/ai-in-healthcare-market-size-worldwide/
2. Habehh, H., & Gohel, S. (2021). Machine learning in healthcare. Current genomics, 22(4), 291.
3. Hwang, H. W., Park, J. H., Moon, J. H., Yu, Y., Kim, H., Her, S. B., … & Lee, S. J. (2020). Automated identification of cephalometric landmarks: Part 2-Might it be better than human?. The Angle Orthodontist, 90(1), 69-76.
4. Kazimierczak, N., Kazimierczak, W., Serafin, Z., Nowicki, P., Nożewski, J., & Janiszewska-Olszowska, J. (2024). AI in orthodontics: Revolutionizing diagnostics and treatment planning—A comprehensive review. Journal of Clinical Medicine, 13(2), 344.
5. Li, P., Kong, D., Tang, T., Su, D., Yang, P., Wang, H., … & Liu, Y. (2019). Orthodontic treatment planning based on artificial neural networks. Scientific reports, 9(1), 2037.
6. Khanagar, S. B., Al-Ehaideb, A., Vishwanathaiah, S., Maganur, P. C., Patil, S., Naik, S., … & Sarode, S. S. (2021). Scope and performance of artificial intelligence technology in orthodontic diagnosis, treatment planning, and clinical decision-making-a systematic review. Journal of dental sciences, 16(1), 482-492.
7. Bartkowiak, T., & Walkowiak-Śliziuk, A. (2018). 3D printing technology in orthodontics–review of current applications. Journal of Stomatology, 71(4), 356-364.
8. Tsoukala, E., Lyros, I., Tsolakis, A. I., Maroulakos, M. P., & Tsolakis, I. A. (2023). Direct 3d-printed orthodontic retainers. a systematic review. Children, 10(4), 676.
9. Alassiry, A. M. (2019). Orthodontic retainers: A contemporary overview. J Contemp Dent Pract, 20(7), 857-862.
10. smarTooth app developer credits: Augusta University
11. smarTooth app link: https://apps.apple.com/us/app/smartooth/id1007662611
12. EXOCAD app link: https://exocad.com/about-us/about-exocad
13. Vadachkoriia, N. R., NSh, G., & Mandzhavidze, N. A. (2007). ” Golden proportion” and its application to calculate dentition. Georgian medical news, (142), 87-94.
14. Muniz, F. W. M. G., Cavalcante, D. J., Moreira, M. M. S. M., Rodrigues, L. K. A., de Oliveira Fernandes, C. A., de Almeida, P. C., & de Sousa Carvalho, R. (2017). Association between confidence in smiling and esthetic characteristics. Journal of Esthetic and Restorative Dentistry, 29(2), E56-E66.
15. Ansari, S., Alsanie, Y., AlOjan, M., AlKhalifah, T., Hafez, A., & Alfadda, A. (2020). Desired smile and effect of facial esthetics on the confidence level of the Saudi public: a survey-based study. Journal of Dentistry and Oral Sciences, 2, 1-20.
16. Dabuke, A. M., Zainal, V. R., & Hakim, A. (2023). The Effect of Self-Ability and Self Confidence on Employee Performance: A Literature Review. Dinasti International Journal of Digital Business Management, 4(2), 286-296.

About the author

Dr. Paul Ouellette, President of the Dental AI Association North America and Chair of the Division of Orthodontics, is a Diplomate of the American Board of Orthodontics and a Clinical Professor of Orthodontics. His leadership and expertise significantly influence the field of dental AI and orthodontics.

The history of artificial intelligence: From ancient times to modern times

by admin | Dec 14, 2025 | AIMEDENT Journal

The history of artificial intelligence (AI) is a fascinating journey that spans centuries, from ancient myths to modern technological marvels. This essay explores the key milestones and developments that have shaped the field of AI.

The roots of artificial intelligence in Mesopotamia and Islamic civilization

Artificial intelligence (AI) might seem like a modern marvel, but its conceptual roots can be traced back to ancient Mesopotamia and the Islamic Golden Age. These civilizations laid the groundwork for algorithmic thinking and computational methods that are fundamental to AI today.

Mesopotamia: The Cradle of Civilization

Mesopotamia, often referred to as the “Cradle of Civilization,” was home to some of the earliest known forms of writing, mathematics, and complex societal structures. The Sumerians, who inhabited this region around 3000 BCE, developed cuneiform writing on clay tablets, which included some of the earliest recorded algorithms. These algorithms were used for various purposes, such as calculating land areas, distributing resources, and astronomical observations¹.

The Babylonians, who followed the Sumerians, made significant advancements in mathematics. They developed a base-60 number system, which is still used today in measuring time and angles. Babylonian mathematicians also created algorithms for solving quadratic equations and other mathematical problems². These early computational methods laid the foundation for more complex algorithmic thinking.

The Islamic Golden Age: A flourishing of knowledge

The Islamic Golden Age, spanning from the 8th to the 14th centuries, was a period of remarkable intellectual and scientific achievements. Scholars in the Islamic world made significant contributions to mathematics, astronomy, medicine, and engineering. One of the most notable figures was Al-Khwarizmi, a Persian mathematician whose works introduced the concept of the algorithm. In fact, the term “algorithm” is derived from his name².

Al-Khwarizmi’s book, “Kitab al-Jabr wa-l-Muqabala,” laid the foundations for algebra. His methods for solving linear and quadratic equations were revolutionary and influenced both Islamic and European mathematics. The translation of his works into Latin in the 12th century played a crucial role in the development of mathematics in the Western world².

Other scholars, such as Al-Kindi and Al-Farabi, made significant contributions to cryptography and logic, which are essential components of modern AI. Al-Kindi’s work on frequency analysis laid the groundwork for modern cryptographic techniques, while Al-Farabi’s explorations in logic and philosophy influenced later developments in computational theory².

The legacy of early algorithmic thinking

The advancements in mathematics and algorithmic thinking in Mesopotamia and the Islamic Golden Age were not isolated achievements. They were part of a continuum of knowledge that has influenced modern computational methods and AI. The early algorithms developed by these civilizations were foundational to the development of more complex mathematical theories and computational techniques.

Today, AI systems rely on algorithms to process data, make decisions, and learn from experience. The historical contributions of Mesopotamian and Islamic scholars to algorithmic thinking are a testament to the enduring legacy of these ancient civilizations. Their work continues to inspire and inform the development of AI and other advanced technologies.

Philosophical foundations

While the concept of artificial beings with intelligence dates back to antiquity, the philosophical foundations of AI were laid much later. In the 17th and 18th centuries, philosophers like René Descartes and Thomas Hobbes began to explore the idea of human thought as a mechanical process, laying the groundwork for future AI research.

The birth of modern AI

The modern era of AI began with the invention of the programmable digital computer in the 1940s. British mathematician and logician Alan Turing played a pivotal role during this period. Turing’s work on the concept of a universal machine, now known as the Turing Machine, laid the theoretical foundation for AI. In 1950, Turing introduced the famous Turing Test, a criterion for determining whether a machine can exhibit intelligent behaviour indistinguishable from that of a human⁴.

The Dartmouth Conference and the birth of AI research

The field of AI research was formally established in 1956 during the Dartmouth Conference, organized by John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon. This conference marked the beginning of AI as an academic discipline. Researchers at the conference were optimistic about the potential of AI, predicting that machines with human-like intelligence would be developed within a few decades³.

Early achievements and challenges

The 1950s and 1960s saw significant progress in AI research. Early AI programs, such as the Logic Theorist and the General Problem Solver, demonstrated the potential of machines to solve complex problems. However, the field also faced challenges. The limitations of early computers and the complexity of human cognition made it clear that creating truly intelligent machines was more difficult than initially anticipated³.

The AI winters

The optimism of the early years was followed by periods of reduced funding and interest, known as “AI winters.” The first AI winter occurred in the 1970s, triggered by criticisms from researchers like James Lighthill and the realization that progress was slower than expected. A second AI winter occurred in the late 1980s and early 1990s, as funding and interest waned once again³.

The rise of machine learning and deep learning

The late 1990s and early 2000s saw a resurgence in AI research, driven by advances in machine learning and the availability of large datasets. Machine learning algorithms, such as neural networks, began to outperform traditional AI methods. The breakthrough came in 2012 with the advent of deep learning, a subset of machine learning that uses neural networks with many layers. Deep learning revolutionized AI, enabling significant advancements in image recognition, natural language processing, and other fields³.

AI in the 21st Century

Today, AI is an integral part of our daily lives. From virtual assistants like Siri and Alexa to autonomous vehicles and advanced medical diagnostics, AI technologies are transforming industries and society. The field continues to evolve rapidly, with ongoing research in areas such as reinforcement learning, generative models, and ethical AI³.

Conclusions

The history of AI is deeply intertwined with the intellectual heritage of Mesopotamia and the Islamic Golden Age. The early algorithms and mathematical advancements from these periods laid the groundwork for the sophisticated AI systems we have today. As we continue to push the boundaries of AI, it is essential to recognize and celebrate the contributions of these ancient civilizations to the field of algorithmic thinking.

Furthermore, the history of artificial intelligence is a testament to human ingenuity and perseverance. From its philosophical roots to the cutting-edge technologies of today, AI has come a long way. As we look to the future, the potential of AI to solve complex problems and improve our lives remains boundless.

References

1. History of artificial intelligence | Dates, Advances, Alan Turing …. https://www.britannica.com/science/history-of-artificial-intelligence.
2. History of artificial intelligence – Wikipedia. https://en.wikipedia.org/wiki/History_of_artificial_intelligence.
3. AI Timeline: Key Events in Artificial Intelligence from 1950-2024. https://www.theainavigator.com/ai-timeline.
4. Artificial intelligence – Wikipedia. https://en.wikipedia.org/wiki/Artificial_intelligence.
5. en.wikipedia.org. https://en.wikipedia.org/wiki/History_of_artificial_intelligence.
6. The Opportunities and Risks of Artificial Intelligence in … – CUSPE. https://www.cuspe.org/wp-content/uploads/2016/09/Hamid_2016.pdf.
7. Lindsay Society to hold conference in Sheeld – Nature. https://www.nature.com/articles/s41415-023-6299-2.pdf.
8. The Democratization of Artificial Intelligence: Theoretical Framework. https://www.mdpi.com/2076-3417/14/18/8236.
9. How artificial intelligence aids ancient history – Prospect. https://www.prospectmagazine.co.uk/ideas/philosophy/language/62344/how-ai-aids-ancient-history.
10. Computing in Early Civilizations – SpringerLink. https://link.springer.com/chapter/10.1007/978-3-030-66599-9_2.
11. History of Iraq – Wikipedia. https://en.wikipedia.org/wiki/History_of_Iraq.
12. History of Mesopotamia | Definition, Civilization, Summary, Agriculture …. https://www.britannica.com/place/Mesopotamia-historical-region-Asia.
13. Groundbreaking AI project translates 5,000-year-old cuneiform at push …. https://www.timesofisrael.com/groundbreaking-ai-project-translates-5000-year-old-cuneiform-at-push-of-a-button/.

About the author

Dr. Ameed Khalid Abdul Hamid, a renowned dentist and global leader in dental aesthetics, has significantly contributed to the integration of artificial intelligence (AI) in dentistry. His pioneering work has not only advanced dental practices but also set new standards and advancements in the field of dental AI, such as in clear aligners and laser treatments and combining halitosis with AI. Dr. Ameed has played a pivotal role in promoting the adaption of AI in dentistry in the Middle East, as the Chairman of the Middle East Branch of the Dental Artificial Intelligence Association (dentalaia.org). Dr. Ameed has been honoured by Queen Elizabeth II and recognized as the “Dentist to the Royals” and “Sheikh of Dentists.” His accolades include numerous awards for his achievements in dental innovation, reflecting his commitment to advancing the field through AI.

Journal of Dental Artificial Intelligence (JDAI)

by admin | Dec 14, 2025 | AIMEDENT Journal

Dear Readers,

It is our great honour to welcome you to the inaugural edition of the Journal of Dental Artificial Intelligence (JDAI) Vol:1.1, a publication dedicated to advancing dental education, technology, and artificial intelligence as part of Oral Health.

At JDAI, our mission is to advance knowledge and drive innovation by publishing rigorous research and insightful contributions from leading experts. As a peer-reviewed journal, JDAI is dedicated to tackling the pressing challenges and exploring the transformative opportunities that artificial intelligence brings to the field of dentistry.

We firmly believe that integrating AI into dental practices has the potential to revolutionize patient care, enhance diagnostic precision, and streamline clinical workflows. Journal of Dental Artificial Intelligence (JDAI) is committed to supporting this transformative journey by disseminating valuable insights and encouraging collaboration within the global dental community.

We invite you to join us in shaping the future of dentistry through pioneering AI advancements that enhance patient care and professional practice. Together, we can lead the way in ensuring that the dental profession remains at the forefront of technological progress.

Thank you for undertaking this exciting journey with us. We look forward to your active involvement and contributions in the issues to come.

Sincerely,
Dr. George Freedman, Editor of the Journal of Dental Artificial Intelligence (JDAI)
JDAI@dentalaia.org

The role of artificial intelligence in dentistry

by admin | Dec 14, 2025 | AIMEDENT Journal

Introduction to artificial intelligence in dentistry

Today, the role of artificial intelligence has become stronger within the field of medicine and dentistry. It is getting difficult to keep up with this change. Many tasks performed by humans for many years are now done by machines with the help of artificial intelligence. The main goal of this transition is to make diagnostics, therapy, and treatment easier, cheaper, and more reliable. Dentistry has revolutionized in terms of practice and treatment with technological development. From digital imaging systems to robotic surgeries, devices offer a wide range of uses in the field of dentistry. Research on artificial intelligence in medicine has shown evidence of its integration in the field. Image recognition-based tasks in dentistry are a part of artificial intelligence. Additionally, deep learning networks, an updated topic of artificial intelligence, can be applied in dentistry to solve predetermined problems automatically by learning from generated data.

Despite the technological advances in the dental field revolutionizing practice, integrating artificial intelligence (AI) in providing dental services is yet to be imminently realized. Still under research and development, AI tools have showcased significant potential in the evaluation and prognostication of dental lesions, especially caries and endodontic conditions. Effective integration of AI tools in dental service provision depends on different agents, including technology providers, demanders of dental services, and the dental workforce. Integrating AI in dentistry should facilitate effective, reliable, efficient, and prompt delivery of dental services. To avoid the limitations that characterized AI application in general health, which widened the digital health divide, it is important to consider these aspects in the conceptualization, design, and utilization of AI systems that target dental care delivery. The main hope of AI lies in effective complementarity with the human workforce in the dental field rather than substitution, especially in light of increasing concerns over the cybersecurity of AI-supported health service provision.

Historical development and evolution of AI in dentistry

Historically, efforts to adopt AI in healthcare have evolved through four phases. The first phase realized the creation of expert-based systems. Next, scientific knowledge in medicine got codified into databases, leading to empirical systems for medicine. Following this was the large-scale connectionist model—artificial neural networks—eventually leading to recent naturalized systems. These evolutionary changes were accompanied by advances in knowledge systems like unified medical language, speech- to-text and voice recognition, and large-scale enterprise-based medical records.

The apogee of these healthcare-related AI advances came with the wins that expert systems scored in backgammon and game shows over their competitors. Even when there are ethical, managerial, and security challenges to be addressed, AI has generated optimism concerning the use of data systems, deep learning, algorithmic systems, natural language processing, computer vision, and data speech in precision medicine, mental care, healthcare logistics, and diagnostics. The rise of AI has seen an increase in the formation of partnerships and coalition deliberations at local and international levels.

Applications of AI in dental imaging and diagnosis

Effective delivery techniques

Radiographic imaging techniques, such as panoramic radiography, intraoral radiography, dental cone-beam computed tomography, and computed tomography, are widely used in dentistry for diagnosis, evaluation of dental anomalies, surgical planning, and pre-operative evaluation. The image quality of these dental imaging techniques affects the accuracy of diagnosis and prognostication of treatment outcomes. Improvements in dental imaging techniques and encouragement of radiographic techniques that reduce radiation exposure are integral to dentistry.

AI can produce advanced dental imaging techniques that enhance diagnosis and prognostication of treatment outcomes. In modern dentistry, we can measure the distance between two points on a dental image, distinguish dental pulp from dentin, identify the area invaded by dental caries, differentiate anatomic landmarks in a patient’s oral cavity, and assess anatomical measurements with a software application of an AI-DL algorithm to radiographic images. In addition to dental and periodontal diagnosis and treatment, AI algorithms that analyze dental and facial morphology show potential applications in orthodontics and maxillofacial surgery. With the development of AI, dental diseases have broadened from simple radiographic diagnosis to patient-specific CBCT image-based 3D navigation. AI-powered 3D navigation for surgery planning of the jawbone proposes advanced digital dentistry. AI-powered dental imaging and diagnosis applications contribute to cost savings in treatments and reduction of dentally relevant radiation dosage. Noteworthily, beyond the advantages of efficiency and reduced cost, medical applications of AI-powered 3D navigation contribute to overall patient safety in planned CBCT imaging. Dental implant placement is one of the most profitable treatments for which AI-powered three-dimensional image navigation has been applied in oral surgery. In summary, AI-powered daily clinical dental imaging and diagnosis may accelerate treatment outcomes for dentists and patient benefits.

Automated image analysis

There have been several approaches used in the regulation of dental image analysis, with the need for increased automation resulting from the increased amounts of data that are being obtained during studies. Whereas previously, time- consuming manual correction was considered common practice, the possibility of automatic correction opens the doors for completely unsupervised image processing. A method using confidence parameters employed a density distribution of reversing voxels using a dataset from two digital dental image receptors. An active contour method was incorporated with earlier methods to handle teeth with poor edge quality. The Hough transform seems to be a popular method for section grouping in the detection of teeth and creating topography maps in CT image data.

Artificial intelligence also plays a significant role in solving certain challenges in dental specialties by offering innovative solutions. An end-to-end AI feature learning-based framework possesses several advantages: it directly uses raw 2D surface and 3D voxel data for feature learning, requires no manual feature engineering, and offers the possibility for automatic image correction in the pipeline. This automatic and adaptive deep learning-based 3D dental image retrieval system automatically rectifies images based on content-aware features to ensure the correct occlusal plane and dental side to derive the feature for image- based image retrieval. It facilitates fast and easy localization of dental-specific structures in the database and offers the ability to maximize patient diagnosis while minimizing radiation exposure during dental diagnosis.

Computer-aided diagnosis

Computer-aided diagnosis is a diagnostic strategy in which an AI algorithm helps support decision-making tasks involving pathologists. The most known and applied example of CAD in dentistry is the identification of dental caries. This type of assistance is essential since an average radiograph of a patient’s skull is very rich in visual information, making manual analysis laborious, slow, and error prone. Moreover, such analysis would have to be performed by highly skilled and experienced radiologists, leading to high costs and slow disease progression analysis. Instead, several studies have shown that AI algorithms can assist dentists by predicting where caries are located, how deep into dentin the caries have advanced, and how the density, i.e., the shade of the image, varies in the carious area. The performance, sensitivity, and specificity of these systems are high, many times surpassing the average human expert.

Another important example of the application of CAD in dentistry is the detection of periodontitis. Dental radiographs are also the most frequently used outputs of this advanced system. A typical periodontitis detection algorithm first locates the boundary of the precise level of the alveolar crest for every tooth, then estimates the angle of the bone resorption, and finally segments accurately the defect. Another symptom that can be identified from dental radiographs is periapical lesions, for example, in the case of an apicoectomy, which is an invasive treatment that unnecessarily decreases the chance of the retention of the dental element.

3D imaging and virtual reality

3D imaging and virtual reality will change how dentists diagnose, plan, and execute dental procedures. The 3D imaging allows accurate representations of extraoral and intraoral structures, sizes, and shapes. It allows dentists to plan the surgical procedures, including implant placement and accurate bone dimension measurements in a virtual environment. The use of the virtual reality system will allow dentists to gain information from the 3D image and integrate augmented reality with holographic images of their patient pathology or anatomical landmarks. The additional advancement of this technology will allow them to assess the movement of the patient’s jaw in real-time integrated with 3D measurement data, which may offer an affordable VR-based solution. This technology cannot only be used by dentists, as is the current trend, where practitioners including oral and maxillofacial surgeons are using VR-based haptic simulation to practice dental surgery; consumers could also utilize the continuous advancement of head-mounted displays. In other words, through this technology, patients could view their virtual tooth and select their tooth shape and shade, eliminating the inexact color selection of traditional dental impressions and 2D photo imaging. Beyond the current application where this technology is used by doctors and patients, dental educators and students could use this technology to provide interactive and immersive learning experiences, transforming the study of the tooth into a study accessing 3D, alongside which the student can walk. These developments in AI will allow smarter imaging systems, offering assistance to the dentistry team while also creating the ideal devices or products that meet a variety of data acquisition needs. Three-dimensional and 4D imaging will evolve and offer dentists a canonical source of specialized data for the treatment of oral diseases.

AI-driven treatment planning and precision dentistry

This study briefly reviewed the potential key roles of AI in oral healthcare and related dental fields. The summary insights generated included (a) the potential transformational role during professional training, practice, and beyond, (b) the intricate engagement of AI technology in multimodality data mining and interpretation, and (c) ethical and societal issues, legal and policy matters, and data stewardship concerns that implore systematic attention. With the occasion of this review, an enhanced consensus for the field of AI applications in dentistry and beyond for a broad and positive public benefit was encouraged.

In an era where big multiscale data size and complexity reign, the potential for a more comprehensive AI-machine learning treatment planning approach for the sake of precision dentistry becomes realistic. Understandably, the AI-driven machine learning approach only sets the perimeter for eventual refinement by a dental professional. However, AI advances unquestionably employ the potential for the metamorphosis of oral health research, the subspecialties therein, and clinical practice. The height of public, patient, and professional expectations for this promising field commands that AI advances be systematically matched to societal and professional trust. Educational institutions, professional organizations, and government develop accordingly to meet these current and future demands.

Teledentistry and remote monitoring

With an increasing demand for dental services and an increased shortage of dental professionals, teledentistry concepts are becoming more popular. It allows for both remote clinical and non-clinical services. These include synchronous and asynchronous confidential and secure clinical information communication technologies between a dental professional and a patient or between dental professionals and among providers. Remote clinical assessment performed through teleconsultation can help in providing necessary care to persons who cannot access it due to distance, isolation, or an existing health condition. The progress made in digital oral imaging and data storage, transmission of digital radiographs, intraoral photographs, and videoconferencing has especially enabled this transition. Teledental diagnostic and treatment advice services have the potential to improve healthcare access and outcomes. These services, whether diagnostic or treatment-based, are classified based on different imaging applications, such as digital imaging, electronic filing of diagnostic information, and the acquisition, storage, and transmission of diagnostic images. With higher levels of diagnostic accuracy, remote communication, and interprofessional referral links, it is becoming an important aspect of mobile health. The success of these new digital tools has a marked influence on their utilization, the corresponding legislation, reimbursement, and patient and provider collaboration, especially compliance with ethical principles and professional standards.

Challenges and ethical considerations in AI integration

As dentists and clinicians, we have a duty to be well-informed about the treatment options available in order to inform, educate, and help our patients make optimal choices. As with most emerging technologies, the integration of AI does not come without its challenges. Failure to ponder potential hazards resulting from the implementation and development of AI systems could lead to a compromise of patient safety where AI systems are integrated to a certain level and allowed to perform at a level that the underlying learning framework will not be able to support. This discussion shall continue with some of the challenges and ethical guidelines that practitioners, regulatory bodies, and those involved in its implementation should consider. Researchers using selective parts of large datasets instead of the entire set are subject to selection bias and risk developing predictive algorithms that do not necessarily represent the entire target population, leading to overfitting: a form of algorithmic bias that may limit the generalizability of the model in the real world. Additionally, biases possessed by clinical experts at the input level may be inadvertently injected into the learning algorithm, thus carrying them through to predictions. Possible solutions to such shortcomings include transparent AI methods. Transparent algorithms open the black box and provide reasons for predictions such as feature visualization or prediction. Sufficient explanations regarding which factors an AI model used to predict a particular outcome can guide the decision to agree or disagree with the ML algorithm’s output. Transparent algorithms for practitioners are a stepping stone to gaining trust in AI.

Future directions and emerging technologies in AI and dentistry

As AI becomes more accurate, costs decrease, and an increased number of studies are successfully implemented, its overall use should increase over time. We anticipate that with AI technology and advanced mobile dental equipment, dental professionals of the future will provide remote diagnostics and systematic information collection, which will aid oral health care in underserved populations. Informatics generated by AI are expected to greatly influence future trends in medicine, including dentistry. There are a few other emerging technology trends that are predicted to have a significant impact in dentistry in general, as well as in biomaterial science and biomechanics, which might be linked to the field of AI and oral informatics. For example, blockchain, a digital transaction protocol that is permissionless, secure, and transparent, will likely have future implications in digitized health care data through interconnected devices and sensors for secure information exchange and to maintain interoperability of unique patient identifiers. Overall, the rapid technological advances in imaging, computing, telecommunication, intelligent systems, and artificial intelligence fields will likely be highly beneficial for the safety and care of future patients. The application of these advanced technologies in dental research and practice would accelerate together with the world’s increasing population, the greying demographic structure, and oral health-related problems, which continually increase the oral health care needs, including the need for artificial teeth, swallowing, speech, and chewing abilities. Researchers are encouraged to embrace these groundbreaking technologies to maximize the efficiency and effectiveness of dental services. Moreover, advances in dental informatics, materials informatics, and oral health-related systems that are enabled by intelligent engineering techniques can contribute to human happiness and the achievement of the Sustainable Development Goals.

The integration of artificial intelligence (AI) into dental practices, particularly in the context of 3D scanning technologies, has garnered significant attention in recent years. This literature review aims to synthesize the evolving landscape of AI applications in dentistry, focusing on its implications for 3D imaging and intraoral scanning.

In their 2020 study, Hung et al.¹ conducted a comprehensive literature search to identify existing applications of AI in 3D imaging within dentistry. Their analysis revealed that while there is a burgeoning interest in this field, methodological concerns persist, particularly regarding the risk of bias in studies. The authors highlighted three primary applications of AI: automated diagnosis of dental and maxillofacial diseases, localization of anatomical landmarks for orthodontic treatment, and enhancement of image quality. Despite the promising advancements, the authors noted that many studies did not validate their AI models on independent datasets, which raises questions about the reliability of the findings.¹

Building on this foundation, Ahmed et al.² provided a systematic review that emphasized the transformative potential of AI in clinical diagnosis and treatment planning within dentistry. Their findings indicated that AI technologies, particularly those employing deep learning and convolutional neural networks, demonstrated high accuracy in various applications, including the detection of malocclusion, classification of dental restorations, and identification of periodontal diseases. This study underscored the ability of AI to enhance precision in routine dental procedures and the integration of facial and intraoral images for comprehensive patient analysis. However, the authors also cautioned that the full potential of AI in dental diagnostics and management remains to be fully realized.²

Most recently, Altalhi et al.³ explored the role of AI specifically in dental implantology, emphasizing its dual-phase operation involving training and testing. The authors reviewed the literature to assess how AI contributes to treatment planning, particularly with cone beam computed tomography (CBCT) scans, which are considered the gold standard in this area. They pointed out that while AI applications in implant dentistry have shown promise, particularly in planning procedures, challenges remain regarding the effectiveness of these technologies in real-world scenarios. The review highlighted the need for further research to validate the utility of AI in enhancing the success and survival rates of dental implants.³

Through this analysis, it becomes evident that while AI presents substantial opportunities for improving the accuracy and efficiency of dental practices, particularly in 3D imaging and scanning, there are critical limitations and methodological concerns that must be addressed to fully harness its potential.

References

1. Hung, K., Wai Kan Yeung, A., Tanaka, R., & M. Bornstein, M., 2020. Current Applications, Opportunities, and Limitations of AI for 3D Imaging in Dental Research and Practice. ncbi.nlm.nih.gov
2. Ahmed, N., Shakoor Abbasi, M., Zuberi, F., Qamar, W., Syahrizal Bin Halim, M., Maqsood, A., & Khursheed Alam, M., 2021. Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry—A Systematic Review. ncbi.nlm.nih.gov
3. M Altalhi, A., S Alharbi, F., A Alhodaithy, M., S Almarshedy, B., Y Al-saaib, M., M Al jfshar, R., S Aljohani, A., H Alshareef, A., Muhayya, M., & H AL-harbi, N., 2023. The Impact of Artificial Intelligence on Dental Implantology: A Narrative Review. ncbi.nlm.nih.gov

About the author
Prof. MUDr. Alaa Abu Shareia, MSc, DSc, Banska Bystrica, Slovakia, 2024.