News & Announcements
Featured News
the most recent stories from the Division
Nearly Half of Americans Use AI to Help Make Health Care Decisions, Poll Finds
Additional News
from the Division
Performance of a Large Language Model on the Reasoning Tasks of a Physician
In a new Science study, Ethan Goh, Evelyn Bin Ling, Jason Hom, Jonathan Chen, and colleagues from Harvard Medical School and Beth Israel Deaconess Medical Center evaluated the OpenAI o1 model against hundreds of physicians across real-world clinical scenarios. The model outperformed both clinicians and prior systems in diagnosis and management, underscoring its growing potential in clinical care.
Division & Research News
Nigam Shah and Paul Bollyky Elected to AAP
Congratulations to Nigam Shah and Paul Bollyky on their election to the Association of American Physicians (AAP). They were recognized among colleagues at the AAP New Member Induction Dinner over the weekend — an honor that highlights their outstanding contributions to academic medicine and research.
Turning AI Promise into Real-World Practice: Stanford AI in Healthcare Leadership and Strategy
In conference rooms and clinics across the country, leaders are asking the same question: How do we move from excitement about artificial intelligence to systems that actually work — safely, responsibly, and at scale? At the Stanford Division of Computational Medicine, a new program aims to answer that question.
The $1 Trillion Problem AI Still Can’t Yet Solve
The invisible layer of healthcare, known as the administrative spending, costs the United States more than $1 trillion every year. Almost 25 cents of every dollar in healthcare. Despite all the excitement around AI, administrative spending remains largely untouched.
*Artwork courtesy of Jennie Ellison*
AI Translation in Healthcare: An Urgent Call For Evidence-Informed Policy Frameworks
In a new BMJ perspective, researchers Chuk Anyaegbuna, Natasha Steele, April Shichu Liang, Stephen Ma, Ivan Lopez, Nymisha Chilukuri, Kavita Patel, Kevin Schulman, & Jonathan Chen warn that AI translation tools are rapidly entering healthcare without adequate oversight — raising risks of uneven performance across languages and widening health disparities.
The Inverse Care Law in the Age of AI – Geographic Disparities in Health Care Technology Access
A new paper in NEJM AI highlights how AI may unintentionally deepen existing health disparities. First author Yeon-Mi Hwang, alongside senior author Tina Hernandez-Boussard, examines how rural communities — despite facing greater health burdens — have less access to the infrastructure needed to implement AI-driven care.
From AI Tool to Clinical Teammate
A new study led by Selin Everett, with senior authors Jonathan Chen & Eric Horvitz, explores how rethinking human-AI collaboration can improve clinical decision-making. Published in Nature Digital Medicine, the multicenter randomized controlled trial found that when physicians and AI reason independently and then combine their perspectives, diagnostic accuracy significantly improves.
Jonathan Chen on AI in Medicine: Promise, Pitfalls, and Practice
AI and the Future of Asian Health: Advancing Precision Medicine Through Human Insight and Technology
In this kickoff session, Dr. Jonathan H. Chen examines how human expertise and AI work together to improve diagnosis, prevention, and treatment—particularly in tackling health disparities, cultural nuances, and underrepresentation in data that impact Asian communities. He also emphasizes the importance of preserving empathy and human understanding at the core of patient care. Drawing on his experience as both a physician and biomedical informatics scientist, Dr. Chen shares how AI is making healthcare more efficient, personalized, and data-driven.
How a Winding Path Led to a Life-Saving Test
