Tuesday, September 15 Sessions (Virtual)
We invite all Conference participants to utilize the Zoom AI Companion during this year's online sessions, which provides private, real-time discussion summaries and answers to participant inquiries, while helping everyone stay engaged with the topics and each other. In the event of a Zoom connectivity problem, please contact the IHER team at IHERConference@mcw.edu.
Attend Sessions in Zoom Events
In order to successfully attend all IHER Conference sessions in Zoom Events, registrants must first be logged into Zoom.
The Zoom Events lobby will open at 8:45 a.m. on Tuesday, Sept. 15.
Morning Sessions
Plenary Speaker Spotlight | Jonathan H. Chen, MD, PhD | 12–1 p.m.
AI in Medicine: Real Magic or Technological Illusions?
Objectives:
- Describe the rapid trajectory of AI performance on medical knowledge and reasoning tasks, and why to plan for where the technology is going rather than where it is today.
- Interpret randomized trial evidence on physician-AI collaboration, including why AI systems alone can outperform physicians using the same AI.
- Recognize common failure modes of clinical AI – hallucination, errors of omission, and deskilling – and strategies to mitigate them.
- Identify near-term AI applications in clinical workflows, from chart summarization to agentic systems, and the evaluation each warrants before deployment.
- Articulate the enduring human elements of medical practice – competence, communication, and character – and critically examine which roles AI may augment or replace.
Jonathan H. Chen, MD, PhD
Associate Professor of Medicine (Computational Medicine) and of Biomedical Data Science
Stanford Healthcare
Dr. Chen leads a clinical informatics research group to empower individuals with the collective experience of the many, combining human and artificial intelligence to deliver better care than either alone. He also serves as Director of Medical Education in Artificial Intelligence for Stanford Medicine. Before his medical training, Dr. Chen co-founded a company to translate his Computer Science graduate work into an expert system used by people around the world. He continues to practice medicine for the concrete rewards of caring for real people and to inspire his work to advance not just the science and technology, but to redefine how we train (and retrain) an entire generation of the healthcare workforce to safely and effectively integrate intelligent systems to reach all patients in need.