2026 Yale Medical AI Symposium

On March 26, 2026, the Yale Center for Clinical Investigation (YCCI) and the Yale Biomedical Informatics and Computing (YBIC) Core co-hosted the Yale Medical AI Symposium at 101 College Street, which is home to the Department of Biomedical Informatics and Data Science (BIDS). The event brought together clinicians, researchers, trainees, and CTSA network partners to discuss responsible AI in medicine.

The morning began with a welcome from Lucila Ohno-Machado, MD, MBA, PhD, Deputy Dean for Biomedical Informatics and Chair of BIDS at Yale School of Medicine, followed by opening remarks from Nancy J. Brown, MD, Dean of the Yale School of Medicine.

The keynote, "Engineering the Future: Data Science, AI and Beyond," was delivered by Susan J. Gregurick, PhD, Associate Director of Data Science at the National Institutes of Health. Dr. Gregurick described NIH's growing investment in AI and highlighted flagship initiatives including Bridge2AI, AIM-AHEAD, and PRIMED-AI. She emphasized that diverse, high-quality real-world data is foundational to trustworthy AI and that earning public trust through ethical, transparent practices is essential to realizing AI's potential in biomedical research.

The symposium continued with four thematic sessions that explored various aspects of medical AI research and practice.

Session I: AI in Clinical Practice, chaired by Allen Hsiao, MD, FAAP, FAMIA, featured presentations on AI applications in cardiovascular medicine, hematology and oncology, neurology, and emergency medicine. Speakers were Rohan Khera, MD, MS; Jeremy Warner, MD, MS; Richa Sharma, MD, MPH; and Andrew Taylor, MD, MHS.

Session II: LLMs, AI Agents, and Applications, chaired by Yize Zhao, PhD, explored the expanding role of large language models and AI agents in clinical and translational settings. Speakers were Andrew Loza, MD, PhD; Jaideep Talwalkar, MD; Yonghui Wu, PhD; and Hua Xu, PhD.

Session III: Multimodal Data—Clinical, Imaging, Genomics, and More, chaired by Chi Liu, PhD, looked at how AI is used with different types of data, such as medical imaging, genomics, and structural biology. Speakers were Georges El Fakhri, PhD; Qingyu Chen, PhD; Thibault Marin, PhD; and Maria Rodriguez Martinez, PhD.

Session IV: Ethics, Privacy, and Implementation in Medical AI, chaired by Jennifer E. Miller, PhD, addressed governance, federated learning, privacy-preserving methods, and responsible AI deployment. Speakers were Yong Chen, PhD; Griffin Weber, MD, PhD; Adrian H. Zai, MD, PhD; and Hyunghoon Cho, PhD.

Panel: Cross-CTSA Collaboration on Medical AI, moderated by Daniella Meeker, PhD, Chief Research Information Officer at Yale New Haven Health System, convened leaders from the CTSA network to discuss infrastructure, governance, and partnership opportunities for scaling medical AI. The panelists were Lee H. Schwamm, MD; Bhramar Mukherjee, PhD; Thomas R. Campion, Jr., PhD; Karthik Natarajan, PhD; and Kristi Holmes, PhD.

The symposium featured two poster sessions throughout the day, showcasing 30 research presentations spanning topics such as ambient AI scribes, AI-guided cancer vaccine design, LLM-based stroke etiology inference, digital twins for radiotherapy, and opioid use disorder phenotyping. The sessions offered attendees dedicated time to engage with presenters and forge new collaborations across institutions.

John Krystal, MD, ended the program by discussing the potential of data-driven science and sharing a quote from Nicolas de Caritat, Marquis de Condorcet (1793): "[All phenomena] are equally susceptible of being calculated, and all that is necessary, to reduce the whole of nature to laws similar to those which Newton discovered with the aid of the calculus, is to have a sufficient number of observations and a mathematics that is complex enough."

YCCI and YBIC thank all speakers, poster presenters, panelists, organizers, and attendees for contributing to the success of this event.