Artificial Intelligence and Its Use in Dentistry

Gary Kaye, DDS Aditya Narayan, MSc Frank Nia, DMD, MSEd


Artificial intelligence (AI) is an emerging and quickly growing branch of technology that will likely have a significant impact on how we practice dentistry in the near future. While still in its infancy, AI will continue to grow over the coming years, becoming more widely adopted and with more resources devoted to its growth. Even now, in other medical professions such as cancer diagnosis and precision medicine, its use is becoming something of a standard. The potential applications of AI not only apply to dental practices through improvements in patient care but also in other areas of the dental ecosystem: laboratories, reimbursements, claims submissions, and practice management, to name a few.

Approaching the subject—and definition—of AI can be a daunting thought, and misconceptions are unfortunately common. In his 2019 book, Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again, Eric Topol defines AI as “the science and engineering of creating intelligent machines that have the ability to achieve goals like humans via a constellation of technologies.”1 The implementation of AI can be accomplished using various mathematical algorithms and approaches, each with the goal of creating software that can simulate learning or problem-solving. The Food and Drug Administration (FDA) defines machine learning (ML) as an AI technique that can be used to design and train software algorithms to learn from and act on data.2 In short, AI/ML technologies can adapt to new information. This can improve efficiency, offer new solutions to existing problems, and form an infrastructure that would have otherwise been impossible in medicine, let alone in the specific field of dentistry.

The first FDA-approved medical device to use AI/ML was released in 2012,3 and as of 2020, more than 64 devices using AI/ML have been approved for use.4 The utility of the devices range from image interpretation to improve the detection of wrist fractures to user guidance in ultrasound procedures.5,6

Several other uses of AI have become mainstream in medicine, such as voice and handwriting recognition. In addition, companies like Caption Health are involved in ultrasound, Paige and PathAI diagnose diseases from pathology slides, and Zebra Medical Vision diagnoses diseases through medical imaging diagnosis. The applications continue to expand as the AI engines improve, offering new possibilities.

AI has the following areas of application in dentistry:

  • Practice management—contactless service options that include face recognition/voice recognition
  • Diagnosis and treatment planning—caries detection and precision medicine
  • Restorative dentistry—aligner design, restoration design, automated quality control, and shade matching
  • Orthodontic tracking—dental monitoring
  • Reimbursement claims

A few companies have reported some success in IOS technology, crown design, and caries detection, but overall, AI is in its infancy when it comes to dentistry.
There are several AI-driven dental informatic companies working actively to obtain (or that have already received) early-stage clearance from the FDA to provide real-time support to clinicians seeing patients.

The primary implication would be improving the accuracy in providing optimal recommendations and, ultimately, optimal care. Most of us clinicians have at one point or another missed something that only became apparent to us at a later date. With AI, we now have the opportunity to dramatically decrease the chance of oversight. Understanding what leads to diagnostic errors is an ongoing process in dentistry, and these tools can help see to an overall reduction in errors.

Imagine a work environment where you walk into an operatory to greet a patient; you start your physical examination; and as you turn back to the diagnostic information on your computer that is collected through the perio chart, photos, radiographs, and other metrics, there are objective and statistically accurate recommendations for you to review. A reliable and seasoned mentor, this tool will be with you as you see every patient—always there to support in your clinical diagnoses. Moreover, this can open up an opportunity to make recommendations on treatments, risks to avoid, and prognoses based on the evidence gathered. We know through research that AI-driven tools can perform significantly better differential diagnoses, which ultimately equates to better patient outcomes. This future requires humility and the appreciation that computers can aid us in being the best version of ourselves. This is where AI can shine to truly help us give the best care.

Dentistry has long had a subjective component in regard to which treatment options are best for teeth. The implications of getting it wrong have typically not been defined as life-or-death—hence, not being important in the spectrum of medicine. The more we are able to platform dentistry as a true specialty of medicine and integrate the oral-systemic relationships, the more we will be able to improve the health of our patients. The sincere goal for all of us clinicians is to provide a level of care that is based on factual data, and with these AI-driven tools, we take one step closer to realizing that goal.

This is arguably the part that excites us the most: a truly objective, ever-dynamic, and accurate lens on how we are diagnosing, rendering care, and producing outcomes. Through a dashboard environment and business intelligence tools, we can understand in real time how we are taking care of our patients. The analysis can uncover the overutilization or underutilization of dentistry related to our ability to diagnose or not diagnose pathology, problems, and/or defects. The potential to understand a large data set in a matter of seconds, revealing the quality of dental care a provider is rendering, is a powerful concept. Areas that are typically gray can suddenly take information from medical history, perio charting, and radiographs to assess the loss of attachment and risks for periodontitis.

When it comes to business development and the trend toward consolidation in the dental field, you can now easily review the charts of a digital practice and look at patterns of overdiagnosis or underdiagnosis, marginal seals on crowns, obturations and apical health, periodontal disease percentage, and other factors. This can instantly and objectively be analyzed and displayed (superimposed) on the radiographs. Companies such as Overjet ( are already providing tools to administrators in dentistry to allow insight into the care providers are rendering to ensure they are compliant and within acceptable guidelines.

We believe that the future for AI integration into the field of dentistry is bright and that our patient care will only improve as we adopt these emerging innovations. But before that happens, the dental industry will require a new crop of entrepreneurial companies, new types of funding sources, and an appreciation and understanding that open systems lead to innovations that will benefit the entire industry. If we can manage that, the possibilities are limitless.

For more on AI, visit the new AI in Dentistry section of Dentistry Today’s website at


  1. Topol, Eric. Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books; 2019.
  2. U.S. Food and Drug Administration. Artificial intelligence and machine learning in software as a medical device. Published January 12, 2021.
  3. Castelletti S, Dagradi F, Goulene K, et al. A wearable remote monitoring system for the identification of subjects with a prolonged QT interval or at risk for drug-induced long QT syndrome. Int J Cardiol. 2018;266:89-94. doi:10.1016/j.ijcard.2018.03.097.
  4. Benjamens S, Dhunnoo P, Meskó B. The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database. NPJ Digit Med. 2020;3:118. doi:10.1038/s41746-020-00324-0
  5. U.S. Food and Drug Administration. FDA permits marketing of artificial intelligence algorithm for aiding providers in detecting wrist fractures. Published May 24, 2018.
  6. U.S. Food and Drug Administration. FDA permits marketing of clinical decision support software for alerting providers of a potential stroke in patients. Published February 13, 2018.

Dr. Kaye graduated from the Columbia University School of Dental Medicine, where he received awards in endodontics, prosthodontics, and geriatric dentistry. He has practiced comprehensive dentistry since 1993 and has built successful multispecialty group practices in and around New York. He is a graduate of the Dawson Academy of Comprehensive Dentistry and has published and lectured on ceramics, occlusion, and the adoption of digital dentistry. He consults with dentists, dental schools, and manufacturers on all aspects of digital dentistry. Dr. Kaye serves as the digital editor for Dentistry Today. He can be reached at

Disclosure: Dr. Kaye reports no disclosures.

Mr. Nayaran is the CEO of BioDental Sciences in New York City, which focuses on creating technology solutions for the dental industry. He has co-founded education technology and enterprise software companies. He also served as an executive at numerous Fortune 500 companies, including the Walt Disney Co. He holds an MSc (Int) Physics degree from the Indian Institute of Technology, Kanpur, India.

Disclosure: Mr. Nayaran reports no disclosures.

Dr. Nia practices general dentistry in Atlanta. He is the chief clinical officer of the North American Dental Group, a dentist-owned, multi-site group of practices. He graduated from the University of Pennsylvania with both DMD and MSEd degrees.

Disclosure: Dr. Nia is an investor in Overjet.

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