# Artificial Intelligence in Dental Medicine ![AI generated tooth](/sites/g/files/omnuum6001/files/styles/hwp_5_4__480x385/public/2025-12/AI-hero.jpg?itok=AjRGx1TK) #### calendar\_today Date and Time **May 20 - August 4, 2026** 09:00AM - 11:00AM EDT [ Register arrow\_circle\_right ](https://cvent.me/W3q38k?utm_source=web&utm_medium=web&utm_campaign=ai_course) ## Understand the technologies shaping the future of dentistry - **Live online sessions:** Wednesdays, 9:00–11:00 AM (ET) for 10 weeks - **Interactive learning:** Lectures, small-group discussions, and case studies - **Experienced instructors:** Leaders in dental education and clinical practice - **Global community:** Connect with dental professionals worldwide This live online course introduces dental professionals to the growing role of artificial intelligence (AI) in dental medicine. Participants will learn how AI is currently used in clinical practice and explore emerging technologies that are shaping the future of dentistry. The course begins with the fundamentals of AI and machine learning in dental and medical contexts. It then examines practical applications in diagnostics, treatment planning, patient management, risk assessment, and outcomes prediction. Real-world case studies highlight how AI-enabled tools can improve diagnostic accuracy, support clinical decision-making, and enhance patient care. Ethical considerations—including responsible use of AI and patient data privacy—are addressed throughout the program. By the end of the course, participants will have a clear understanding of how to evaluate and integrate AI technologies into clinical practice. school [### Faculty ](#faculty) people [### Who should enroll ](#enroll) email [### Contact us ](mailto:hsdm_ce@hsdm.harvard.edu) ![headshot](/sites/g/files/omnuum6001/files/styles/hwp_3_4__480x640/public/2026-03/IMG_1742.JPG?itok=ltt-GcNI) This is an extremely innovative program that brings together experts from multiple disciplines and prepares clinicians for the future of AI-augmented medicine. Dr. Laurent Allouche | Montpellier, France Class participant in Cohort 1 ## What you'll learn In this course, participants will explore the growing role of artificial intelligence in dental medicine and its practical applications in clinical practice. Participants who complete this program will be able to: - **Describe** the fundamental concepts of AI in the context of dentistry - **Evaluate** the benefits and limitations of AI-enabled tools in clinical practice - **Assess** strategies for integrating AI into clinical workflows - **Develop and communicate** a framework for applying AI in their own practice and patient care #### Course modules Explore the core topics covered throughout the program. ### Module 1 — Core Concepts of Artificial Intelligence in Dentistry expand\_more This module provides an overview of the fundamental concepts of artificial intelligence (AI), including a brief historical background to contextualize its current relevance in dentistry. Participants are introduced to machine learning (ML) and its distinguishing features compared to more traditional statistical approaches and the human clinical reasoning process. The module also outlines key modeling approaches through which AI is applied within clinical dentistry, dental education, and research. ### Module 2 — Augmented Diagnostics and Computer Vision expand\_more Based on the ubiquitous nature of imaging in dentistry, computer vision is arguably the most relevant AI application in the field. In this deep dive module, participants are introduced to the technical background of computer vision, including deep learning and neural networks. Real-world applications are explored through demonstrations of FDA-cleared algorithms, offering participants a clear view of current capabilities and limitations. The module is complemented by a *workshop* guiding participants through the first steps of developing their own computer vision projects, as well as a *case study* showcasing commercial computer vision solutions currently available on the market. ### Module 3 — Precision Dentistry and Prognostic Modeling expand\_more This module explores the integration of AI in precision dentistry, focusing on the development and application of prognostic modeling for patient-specific treatment planning. Participants will gain insight into AI-driven risk assessments, predictive analytics, and their role in improving long-term treatment outcomes. Key topics include the fundamentals of data collection, training predictive models, and ethical considerations in AI implementation. Participants will learn how prognostic models can enhance clinical decision-making, addressing challenges in dental treatment planning and enabling personalized care pathways. ### Module 4 — Large Language Models and Generative AI expand\_more This module focuses on the technological background and real-world applications of generative AI in dentistry, with a particular emphasis on patient communication and dental education. Participants will gain an understanding of the underlying principles (e.g., auto-regressive prediction) used in generative AI. They will further explore how large language models (LLM) and text-to-image models can enhance patient interactions and clinical workflows while addressing potential pitfalls, including hallucinations. A *case study* by a Harvard research group complements this module, demonstrating generative AI’s potential to revolutionize teaching and learning in dental medicine. ### Module 5 — Future Perspectives expand\_more The aim of this module is to inspire the participants’ understanding of AI to go beyond replicating human diagnostics and uncover hidden insights. Participants will explore innovative new approaches in clinical dentistry, oral and maxillofacial surgery, as well as translational biomedical research. Participants will engage with ethical and philosophical considerations, examining the impact on medical responsibility, intellectual property, and the evolving role of clinicians. The module also addresses the broader implications of AI’s integration into decision-making processes, challenging traditional boundaries of human expertise in clinical practice. ### Dentists’ #1 question about AI “I’m a dentist who wants to learn about AI — where do I begin?” In this quick video, Dr. Balazs Feher shares how the CE course answers exactly that. [ Hear from Dr. Feher arrow\_forward ](https://www.youtube.com/shorts/Kzvx3HyRKRM?feature=share) ![headshot](/sites/g/files/omnuum6001/files/styles/hwp_1_1__480x480/public/2025-12/0088_1115_HSDM_088.JPG?h=75e0a9c1&itok=zgnnU2AO) ## Meet the faculty *Additional instructors will be announced soon.* [### Sung Eun Choi ](/people/sung-eun-choi)Assistant Professor of Oral Health Policy & Epidemiology ![Sung Choi](/sites/g/files/omnuum6001/files/styles/hwp_4_5__690x865/public/2025-01/Sung%20Choi.jpeg?itok=KIwAo7MG) [### Balazs Feher ](/people/balazs-feher)Assistant Professor of Oral and Maxillofacial Surgery ![Dr. Balazs Feher's headshot](/sites/g/files/omnuum6001/files/styles/hwp_4_5__690x865/public/dental/files/balazs_feher.jpg?itok=mL59WESN) [### Magda Feres ](/people/magda-feres)Chair of the Department of Oral Medicine, Infection, and Immunity ![Dr. Magda Feres](/sites/g/files/omnuum6001/files/styles/hwp_4_5__690x865/public/dental/files/feres_headshot.jpg?itok=ixEgP6Rf) [### William V. Giannobile ](/people/wiliam-v-giannobile)Dean and A. Lee Loomis, Jr. Professor of Oral Medicine, Infection, and Immunity Harvard School of Dental Medicine ![Headshot of Dean William Giannobile](/sites/g/files/omnuum6001/files/styles/hwp_4_5__690x865/public/2024-07/Dean-Giannoible.jpg?itok=n0A5touc) [### Fernando Guastaldi ](/people/fernando-guastaldi)Assistant Professor of Oral and Maxillofacial Surgery ![headshot](/sites/g/files/omnuum6001/files/styles/hwp_4_5__690x865/public/2026-02/IMG_4735.jpg?h=b3b4d7fa&itok=WQxzZe32) ## Invited speakers ![headshot](/sites/g/files/omnuum6001/files/2025-12/Manrai%20.jpg) ### Arjun (Raj) Manrai Dr. Arjun (Raj) Manrai is an assistant professor in the Department of Biomedical Informatics at Harvard Medical School, where he leads a research lab focused on applying machine learning and statistical modeling to improve medical decision making. He is also a founding deputy editor of *NEJM AI*, the artificial intelligence-focused journal from the publishers of the *New England Journal of Medicine*, and co-host of the *NEJM AI Grand Rounds* podcast. Manrai’s research areas include the role of artificial intelligence in medical diagnosis, clinical use of genomic data and blood biomarkers, inherited heart and kidney disease, population-level decision-making, and reproducibility and safety in medical AI. His work has been published in the *New England Journal of Medicine* and *JAMA*, presented at the National Academy of Sciences, and featured in the *New York Times*, *Wall Street Journal*, and NPR. He is also deeply involved in undergraduate mentorship at Harvard College, having served for over a decade as a resident tutor and now as a member of the Senior Common Room at Leverett House. Students from his lab have received prestigious honors including the Rhodes and Paul & Daisy Soros Fellowships to continue their training and research in machine learning and medicine. Manrai earned an AB in physics from Harvard College and a PhD in bioinformatics and integrative genomics from the Harvard-MIT Division of Health Sciences and Technology. --- ![headshot](/sites/g/files/omnuum6001/files/styles/hwp_1_1__360x360_scale/public/2025-10/Flavia.jpg?itok=CKS4PQaL) ### Dr. Flavia Teles Dr. Flavia Teles is a professor in the Department of Basic and Translational Sciences at the University of Pennsylvania School of Dental Medicine. Her work focuses on clinical and translational periodontal research, with an emphasis on the oral microbiome and biomarkers of periodontal disease progression. As a professor and core member of the Center for Innovation and Precision Dentistry (CiPD), she is advancing efforts to identify markers of disease initiation and progression and to develop AI-driven tools for personalized periodontal care through the integration of microbiology, immunology, and informatics. She leads a research program dedicated to understanding how the oral microbiome influences periodontal health and treatment outcomes. Her work has been supported by NIH/NIDCR, foundations, and industry partners for more than a decade. In addition to her research activities, Teles contributes to the field through several national and international leadership roles. She serves as an associate editor for the *Journal of Clinical Periodontology*, is a member of the editorial board for the *Journal of Periodontology*, and participates in the American Academy of Periodontology’s Diagnostic Technologies and Precision Medicine Workgroup and its Task Force on Design and Analysis in Oral Health Research. --- ## Eligibility and enrollment details Who should enroll? - Dental clinicians interested in integrating AI into their practice - Academic researchers exploring AI applications in dental medicine - Oral health professionals with limited or no prior exposure to AI - Dental educators seeking to understand and teach AI concepts Tuition Certificate ## Tuition **$3,500 per participant** Register by May 15, 2026, or before capacity is reached—spots are limited. - Payment is due within 30 days of enrollment or prior to the program. - Cancellations submitted in writing at least 14 days in advance are eligible for a full refund. - Institutions interested in enrolling 3+ participants may contact us for discounted group pricing options. ## Certificate Upon completion of the program, participants will receive a verified certificate of completion from Harvard School of Dental Medicine Executive Education. This program is not accredited by any national or local accreditation body. This certificate is not the same as a postgraduate program certificate awarded to full-time postgraduate students in specialty programs as a qualification for recognition by the American Dental Association, nor is it considered in the United States as evidence of advanced study or recognition of specialty training. The program helped me understand how artificial intelligence can support clinical reasoning, rather than simply automate tasks. ## Enroll today! Limited spots available—**registration closes May 15, 2026**, or when full. Have questions about the program? We’re here to help. [ arrow\_forward Register today! ](https://cvent.me/W3q38k?utm_source=hsdm_website&utm_medium=web&utm_campaign=ai_course_footer) [ draftsEmail HSDM Continuing Education](mailto:hsdm_ce@hsdm.harvard.edu) See also:- [ Extended\_learning ](/event-categories/extendedlearning) Save: [ Add to calendar calendar\_today ](https://www.hsdm.harvard.edu/node/1595741/event-feed.ics) Copy link link