2025
12:00 pm - 1:00 pm
Monday Mon
Leadership Lunch & Learn: AI in Medicine - Real Magic or Illusions?
Virtual via Zoom
Pandora’s box has opened in the form of publicly available generative AI systems for every imaginable (and many unintended) purposes.
With a global scarcity of medical expertise against the unlimited demand of people in need, AI's potential to democratize healthcare knowledge, access, and to recover efficiencies is desperately needed.
The implications are vast as we converge upon a point in history where human vs. computer generated content can no longer be reliably distinguished.
This session will review the attention and intention required for AI applications in the high-stakes world of healthcare as we distinguish real magic from convincing illusions.
Learning Objectives
#1 Identify existing and emerging tools that can be used within daily and clinical workflows (e.g., document drafting and summarization tools)
#2 Describe the progression from auto-complete to large language model systems demonstrating surprising emergent properties
#3 Describe and identify the dangers of AI confabulation / hallucination, and the increasing unreliability of distinguishing real vs. fabricated computer generated information.
#4 Recognize the progressive trends of increasing computer capabilities to tackle traditionally human cognitive tasks, and the relative important roles for both in modern healthcare.
Speaker
Jonathan H. Chen MD, PhD
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.