The Artificial Intelligence Dental Laboratory (AI Dental Lab) at the TUSDM Department of Public Health and Community Service (PHCS) is committed to advancing data sciences and AI in health care, dental education, research, and clinical practice.
Established via a generous gift from Beyond Limits, the lab’s goal is to develop smart AI-powered technologies that facilitate the delivery of effective dentistry but also to ensure ethical standards, responsible use, and proper evaluation of existing AI applications.
As a teaching institution, we also focus on educating future dentists and faculty members, offering the ability to critically assess AI models, understand their context, and apply them effectively in dentistry. Our commitment is to ensure that AI-driven advancements enhance patient care, while maintaining transparency, reproducibility, auditability, safety and trust.
We envision a future where data-driven, AI-powered, evidence-based health care strategies advance all aspects of operations to improve individual patient outcomes, access to care, and the health of the community.
Our mission is to develop and integrate AI-based innovation into health care and clinical dental practice, research, and education, with the aim of delivering superior patient care.
AI in Dental Education & Training
For Tufts Dental Students
Our group is involved in multiple educational activities, aimed to teach dental students and existing practitioners how to incorporate AI in clinical dentistry in order to improve quality of care, enhance personalized preventive methods, and make dental offices more efficient.
For Dental Professionals
Continuing Education (CE) Workshops: To ensure that AI becomes an integral part of Dentistry, we offer national and international CE workshops that train dental professionals in AI applications, ensuring they stay ahead of the evolving landscape of digital dentistry. Our CE courses range from 1-day introductory courses to more advanced 4- or 5-day courses. Our CE offerings are described as low-code or no-code and require no prior knowledge of programming.
Ongoing Research Initiatives
The areas of interest we are pursuing today will shape the world of dental health tomorrow.
We are developing deep learning algorithms that enhance radiographic interpretation, improving early detection of dental caries, periodontal disease, and oral pathologies.
This initiative engages students and faculty in research, utilizing diverse datasets from Tufts University Dental Care Center, community health centers, and private practices to ensure robust, bias-free diagnostics.
Faculty Lead: Hend Alqaderi
Participating Faculty:
Our research explores the application of natural language processing (NLP) to automate and standardize dental diagnostic coding. AI models analyze electronic dental records (EDRs) and clinical notes, ensuring accurate classification of conditions, treatments, and billing codes, ultimately improving documentation efficiency and patient care.
Faculty Leads: Hend Alqaderi and Athanasios Zavras
We investigate the role of AI in analyzing the oral microbiome’s impact on systemic health.
By integrating genomic sequencing data with machine learning models, we aim to predict disease susceptibility and tailor preventive strategies to individual patient profiles, fostering a personalized approach to oral health care.
This project is funded by Dasman Diabetes Institute in Kuwait.
Faculty Lead: Hend Alqaderi
Reflecting on 30+ years of experience in the field, we aim to develop point-of-care salivary prognostics and diagnostics for a variety of conditions, such as head and neck cancer, osteonecrosis of the jaw, dental caries, periodontal disease, as well as several systemic conditions that are detected in saliva. Machine learning is the common denominator in our discoveries platform.
Faculty Lead: Athanasios Zavras
Generously funded by the CareQuest Foundation, this project aims to develop optimization algorithms for better triaging the patients of the Tufts Special Care Dental Clinics.
The overall goal is to improve the efficiency of our seven dental clinics in order to increase our capacity to serve.
Faculty Lead: Athanasios Zavras
Participating Faculty:
We are building a comprehensive oral health data repository to support AI-driven research.
By aggregating and structuring large-scale datasets, we enable researchers to develop innovative AI applications that enhance:
- Diagnostics
- Treatment planning
- Overall patient outcomes
Faculty Leads: Hend Alqaderi and Athanasios Zavras
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