2026 Yale Medical AI Symposium

Overview

About the Symposium

The Yale Center for Clinical Investigation (YCCI) and the Yale Biomedical Informatics and Computing (YBIC) Core at Yale School of Medicine invite participation from Clinical and Translational Science Award (CTSA) hubs and medical AI experts to a one-day Medical Artificial Intelligence (AI) Symposium. In person attendance is expected from US East Coast participants.

The symposium will bring together investigators, clinicians, informaticians, data scientists, and trainees to share advances in medical AI, foster cross-CTSA collaboration, and discuss best practices for developing, evaluating, and deploying AI in clinical and translational research.

We invite CTSA-affiliated institutions to attend and to submit poster presentations highlighting ongoing or completed work at the intersection of AI, informatics, clinical and translational science.

Date & Location

Date:

March 26th 2026
8am-4pm, followed by a reception

Location:

101 College St,
New Haven, CT 06510
(in-person for presenters and audience, remote for those who want to attend only)

Symposium Objectives

Highlight innovative AI methods and applications in clinical and translational research

Promote collaboration and knowledge exchange across CTSA hubs

Discuss challenges related to data quality, governance, reproducibility, and responsible AI

Identify opportunities for multi-site studies and shared CTSA AI infrastructure

Call for Posters · Closed

Call for Posters

We welcome abstracts describing research, methods, platforms, tools, or real-world use cases relevant to medical AI. Submissions may represent early-stage concepts, ongoing projects, or mature implementations. Poster presenters must attend in person.

Submit Abstract

Registration & Agenda

Please note that panel details and speakers may be subject to change.

7:00 AM – 8:00 AM

Registration & Continental Breakfast

Check-in and Networking
Light Breakfast provided
Posters may be set up during this time

8:00 AM – 8:15 AM

Welcome & Opening Remarks

8:15 AM – 9:00 AM

Keynote Presentation

9:00 AM – 10:00 AM

Thematic Session I: AI in Clinical Practice

Session Chair

Allen Hsiao, MD, FAAP, FAMIA

Professor of Pediatrics (Emergency Medicine) and of Biomedical Informatics & Data Science, Yale School of Medicine; Chief Health Information Officer, YNHHS

Speakers

Rohan Khera, MD, MS

Associate Professor of Cardiovascular Medicine; Director of Cardiovascular Data Science Lab, Yale School of Medicine

“Transforming Cardiovascular Care and Accelerating Discovery with Artificial Intelligence”

10:00 AM – 10:15 AM

Coffee Break

Refreshments & Networking

10:15 AM – 11:15 AM

Thematic Session II: LLMs, AI Agents, and Applications

Session Chair

Yize Zhao, PhD

Associate Professor of Biostatistics and Associate Professor of Biomedical Informatics & Data Science, Yale School of Public Health

Speakers

Andrew Loza, MD, PhD

Instructor of Biomedical Informatics and Data Science; General Pediatrics, Yale School of Medicine

“Multimodal Medical Foundation Models for Risk Prediction and Treatment Effect Estimation”

11:15 AM – 12:15 PM

Thematic Session III: Multimodal Data: Clinical, Imaging, Genomics and more

Session Chair

Chi Liu, PhD

Professor of Radiology and Biomedical Imaging, Yale School of Medicine; Associate Director of Biomedical Imaging Technology, Yale Biomedical Imaging Institute; Director for Research Faculty Affairs, Radiology & Biomedical Imaging

Speakers

Georges El Fakhri, PhD, DABR

Director, Yale Biomedical Imaging Institute; Director, Yale PET Center; Vice-Chair; Professor of Radiology & Biomedical Imaging; Professor of Biomedical Informatics & Data Science, Yale School of Medicine

“Successes and Challenges of Deep Learning in Medical Imaging”

12:15 PM – 1:30 PM

Poster Session 1 & Lunch

Open Seating
Poster Discussions & Networking

Presenter	Poster Title
Kent Mccann	Continuous-Value Tokenization Improves Medical Foundation Model Performance
Shawn Wahi	Predicting Renal Cell Carcinoma Outcomes from Clinical Trial Data Using Multimodal Genomic Foundation Models
Muhammad Munshi	NursePT: Evaluating Patient Engagement with a Voice-Enabled AI Assistant in Facial Plastic Surgery
Nicholas Wells	Building an AI Platform for Intraoperative Neural Analysis: A Validated Pilot in Vascular Care Quality Improvement
Maureen Canavan	Understanding the Role of Uncertainty Quantification in Cancer Mortality Prediction: A Real-World Study
Oscar Murillo Gomez	An AI-Guided In Silico Decision Engine for Prioritizing CRISPR/Cas9-Based Cancer Vaccine Targets from Tumor Genomics
Ashti Shah	Urology Copilot: Customizing Large Language Models to Clinical Algorithms for Safer, Evidence-Based Clinical Decision Support
Xinyu Wei	Decoding mRNA Quality with ctDNA Foundation Model: Quantifying Long-Read vs. Short-Read Sequencing Bias Using Drug-Likelihood Boosting
Katie Howard	Standardizing NF2-Related Schwannomatosis Surveillance Using AI-Based 3D Tumor Segmentation
Shanin Chowdhury	Impact of an Ambient AI Scribe on Resident Physician Experience and Documentation Burden: A Pre-Post Quality Improvement Study
Alec Rutherford	Large Language Models and Counseling for Therapy 13 and 14
Tianxiao Wei	AI-Driven Estimation of Patient Out-of-Pocket Costs
Jianxiang Gao	When Domain-Specific Diseases in Large Language Models: Diagnosing and Adapting Learned Representations via Modularized Transformer Decoding
Richa Sharma	Application of a Large Language Model to Infer Ischemic Stroke Etiology and Elucidating its Diagnostic Reasoning
Alex Choi	ChatGPT vs. Physician: Quality and Wellness Calibration of Certifications of Terminal Illness

View Accepted Posters →

1:30 PM – 2:30 PM

Thematic Session IV: Ethics, Privacy, and Implementation in Medical AI

Session Chair

Jennifer E Miller, PhD

Co-Director, Program for Biomedical Ethics; Associate Professor of Medicine (Internal Medicine), Yale School of Medicine

Speakers

Yong Chen, PhD, FASA, FACMI

Professor of Biostatistics; Senior Scholar at Center for Clinical Epidemiology & Biostatistics, University of Pennsylvania

“Empowering Your Study Via Federated Learning Using PDA”

2:30 PM – 3:30 PM

Panel: Cross-CTSA Collaboration on Medical AI

Moderator

Daniella Meeker, PhD

Associate Professor of Biomedical Informatics & Data Science, Yale School of Medicine | Chief Research Information Officer, Yale New Haven Health System

Panelists

Lee H. Schwamm, MD

Associate Dean, Digital Strategy & Transformation, Professor in Biomedical Informatics & Data Science and Professor of Neurology, Yale School of Medicine | Senior Vice President & Chief Digital Health Officer, Yale New Haven Health System

3:30 PM – 3:35 PM

Closing Remarks

Speaker

John Krystal, MD

Robert L. McNeil, Jr. Professor of Translational Research and Professor of Psychiatry, of Neuroscience, and of Psychology; Chair, Department of Psychiatry; Physician-in-Chief of Psychiatry, Yale New Haven Hospital; Co-Director, Yale Center for Clinical Investigation

“Closing”

3:35 PM – 5:00 PM

Poster Session 2 & Networking Reception

Light Refreshments Provided
Poster Discussions & Networking

Presenter	Poster Title
Garrett Ash	Leveraging AI for Digital Phenotyping: Anticipating Lapses in Exercise for Adults with Type 1 Diabetes
Huan Li	Implementation of an Opioid Use Disorder (OUD) Machine-Learning Classifier in Real-Time Clinical Workflow for the ADAPT Clinical Trial
Yukang Zeng	Power Agent: A Collaborative Multi-Agent Framework for Causal Power Analysis and Sample Size Determination
Raghavee Neupane	Artificial Intelligence in Medicine: What Works, What Hinders, and Why It Matters
Varada Khanna	Automating Neurological Scoring for Parkinson's Disease Patients using LLM-Based Analysis of Patient-Clinician Interactions
Shivi Kumar	Physics-Informed Neural Networks Reveal Stability Thresholds Underlying Mechanistic Resistance in Glioblastoma
Lovedeep Dhingra	Single-Lead ECG-App from Wristbands as a Device-Agnostic Digital Biomarker of Cardiovascular Risk: Multisite and Prospective Validation
Anvi Sud	A Patient-Specific Digital Twin for Adaptive Radiotherapy of Near-Small Cell Lung Cancer
Oscar Murrilo Gomez	AI-Guided Design and Prioritization of Tandem Neoantigen Sequences for Melanoma CDM Cancer Vaccines
Oana Sandu	Optimizing Artificial Intelligence Analysis of Social Determinants of Health from Neural Networks Tools to Enable Risk Stratification and Outcomes
Madeline Daquila	Who Lives, Who Dies, Who Tells Your Story: Operationalizing Sociohistorical Connectivity in NLP for Structural Reviews in Major Elective Surgery
Julia Fu	Evaluation of an Autonomous AI System for Multimodal Diabetic Retinopathy Screening across a Community University-Qualified Health Center
Morgan Hardy	Artificial Intelligence-Assisted Cognitive Medial Modules with Ketamine for Treatment-Resistant Depression
Tyger Lin	Identifying Pancreatic Cysts and their Malignant Potential in Electronic Medical Records Using NLP and LLM
Walter Mathis	Automated Scoring and Automated Categorization of Long Feud Clinical Interviews Using AI and Large Language Models