Friday, August 8, 2025
Jay Patel, Ph.D., will present "From Silos to Synergy: Linking Dental and Medical Data to Advance Precision Oral Health" from 12:00 p.m.–1:00 p.m. EDT.
About the Seminar
Dr. Jay Patel is a clinician-scientist uniquely trained in both dentistry and informatics/computer science. As the Director of Artificial Intelligence (AI), Data Science, and Informatics, he leads efforts to reuse and integrate real-world data including linked medical-dental electronic health records (EHRs/EDRs) and social determinants of health (SDOH) to develop clinical decision support systems that enable early diagnosis, prediction, and prevention of disease. Dr. Patel has engineered AI-based algorithms that connect disparate clinical records and developed more than 40 natural language processing pipelines to extract diagnostic and phenotypic information from free-text clinical notes. Moreover, he has developed algorithms that can predict diagnoses using metadata. These efforts exemplify “clever ways to reuse data,” aligning directly with the mission of the NIH Data Sharing and Reuse Seminar Series to showcase innovative uses of existing datasets.
Dr. Patel has developed 13 CDSS using multi-modal datasets. See below the functionality of some of the CDSS and their alignment with the NIH’s Data Sharing and Reuse mission.
Creative and impactful reuse of existing data
Linked dataset infrastructure: Dr. Patel has created a unique dataset of 147,382 patients with linked EHR/EDR, demonstrating impactful reuse of EHR data to explore oral-systemic health relationships and treatment outcomes.
Risk assessment models: He has developed risk assessment models that repurpose longitudinal EHR data to predict the future risk of oral cancer, periodontal disease, and dental caries.
Geospatial analytics: He has applied geospatial analytics to reuse patient and community-level data, mapping oral health trends across Philadelphia and identifying area-level factors contributing to oral health disparities.
Feature reduction tool: Dr. Patel has developed feature reduction tools that reuse complex EHR data to condense hundreds of clinical variables into streamlined predictors for statistical and machine learning models.
Alignment with FAIR data principles
Real-time health information exchange (HIE): The HIE tool enhances data Accessibility and Interoperability between medical and dental care teams by enabling real-time viewing of diagnoses and oral health status across systems.
Natural language processing: The NLP programs make unstructured clinical notes Findable and Reusable by converting them into structured, machine-readable formats that can be shared and reused across studies.
Feature reduction tools: The feature reduction tools improve the reusability and interoperability by creating streamlined variable sets that can be applied across machine learning pipelines and clinical research.
Case studies showcasing clever, cross-disciplinary approaches (AI, informatics, metadata-driven research)
Diagnostic models: Dr. Patel has developed both diagnostic and prognostic prediction models by analyzing multimodal datasets, including linked medical-dental EHRs, social determinants of health (SDOH), and radiographic imaging. These AI-powered systems provide objective, automated diagnoses for periodontal disease and dental caries. By integrating diverse data sources, the models enable interdisciplinary teams to assess risk factors comprehensively and support a holistic approach to patient care, moving beyond siloed, condition-specific treatment.
Risk assessment models: Dr. Patel’s risk assessment models help physicians assess patients’ oral health risks and dentists evaluate systemic health risks. These models identify high-risk patients, enabling both disciplines to implement timely, preventive care strategies and improve overall health outcomes.
Dr. Patel has made significant scholarly contributions to the dental AI community, serving as Principal Investigator on NIH K08, New Jersey Health Foundation (NJHF), and CareQuest grants. He also leads the AI-specific aim as a Co-Investigator on a U01 award. His work has resulted in 54 peer-reviewed publications and 47 conference abstracts across dental, informatics, and computer science journals.
Dr. Patel is the principal investigator on multiple NIH-NIDCR grants, including a K08 and a U01, and holds additional funding from foundations such as Robert Wood Johnson, William Butler, New Jersey Health, and CareQuest. His team has published over 41 peer-reviewed articles and 38 conference abstracts in dental AI and holds a U.S. patent on algorithmic linking of health records. He has also been recognized with prestigious awards, including the AADOCR William Clark Fellowship, William Bulter Award, MIND the FUTURE, and the American Dental Association's David Whiston Leadership Award for his pioneering work in dental AI.
About the Speaker
Jay Patel, Ph.D. Clinician-scientist and Director of AI, Data Science, and Informatics at Temple University Kornberg School of Dentistry
Dr. Jay Patel is a clinician-scientist and Director of AI, Data Science, and Informatics at Temple University Kornberg School of Dentistry. He is among the few in the U.S. formally trained in both dentistry and informatics/computer science. His research focuses on reusing and integrating real-world data, including linked medical-dental electronic health records (EHR/EDR) and social determinants of health (SDOH), to develop clinical decision support systems (CDSS) for early diagnosis and prevention.
Dr. Patel has created a linked dataset of over 147,000 patients and developed 13 CDSS tools that reuse multimodal data for risk assessment, diagnosis, and health information exchange. His work exemplifies the NIH’s mission to promote creative reuse of data, alignment with FAIR data principles, and cross-disciplinary innovation in AI and health informatics. Examples include algorithms for real-time medical-dental data sharing, predictive models for oral cancer and periodontal disease, geospatial analyses of health disparities, and NLP pipelines that transform unstructured clinical notes into reusable datasets.
He has served as PI and Co-I on multiple NIH-NIDCR and foundation grants (K08, U01, NJHF, CareQuest), published over 50 peer-reviewed papers, and holds a U.S. patent. He has been honored with awards such as the ADA David Whiston Leadership Award and the AADOCR William Clark Fellowship for his leadership in dental AI.
About the Seminar Series
The seminar is open to the public and registration is required each month. Individuals who need interpreting services and/or other reasonable accommodations to participate in this event should contact Allison Hurst at 301-670-4990. Requests should be made at least five days in advance of the event.
The National Institutes of Health (NIH) Office of Data Science Strategy hosts this seminar series to highlight examples of data sharing and reuse on the second Friday of each month at noon ET. The monthly series highlights researchers who have taken existing data and found clever ways to reuse the data or generate new findings. A different NIH institute or center will also share its data science activities each month.