APRIL 29 | Jonathan Chen
APRIL 29 | Jonathan Chen
Tuesday, April 29, 202512:40 PM - 2:00 PM (Pacific)
Stanford Law School Building, Manning Faculty Lounge (Room 270)
559 Nathan Abbott Way Stanford, CA 94305
Join the Cyber Policy Center on April 29th from 1PM–2PM Pacific for a seminar with Jonathan H. Chen MD, PhD, Assistant Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science at Stanford University. It will be moderated by Jeff Hancock.
Stanford affiliates are invited to join us at 12:40 PM for lunch, prior to the seminar. The Spring Seminar Series continues through the end of May; see our Spring Seminar Series page for speakers and topics.
About the Speaker:
Jonathan H. Chen MD, PhD leads a research group to empower individuals with the collective experience of the many, combining human and artificial intelligence approaches to deliver better care than either alone. Dr. Chen continues to practice medicine for the concrete rewards of caring for real people and to inspire this research focused on discovering and distributing the latent knowledge embedded in clinical data.
Before his medical training, Chen co-founded a company to translate his Computer Science graduate work into an expert system for organic chemistry, with applications from drug discovery to an education tool for students around the world. His expertise is regularly featured in popular press outlets with over 100 publications in leading clinical and informatics venues and awards from the NIH, National Library of Medicine, American Medical Informatics Association, International Brotherhood of Magicians and more.
In the face of ever escalating complexity in medicine, informatics solutions are the only credible approach to systematically address challenges in healthcare. Tapping into real-world clinical data like electronic medical records with machine learning and data analytics will reveal the community's latent knowledge in a reproducible form. By delivering this back to clinicians, patients, and healthcare systems as clinical decision support, he aims to uniquely close the loop on a continuously learning health system.