Translational AI in Medicine: Unlocking AI’s Potential in Health Care with Nigam Shah

episode

NEJM AI Grand Rounds not yet transcribed

▲ 0

Transcript

This episode hasn't been transcribed yet Upvotes decide what gets transcribed next — 0 so far. Sign in to upvote

More from NEJM AI Grand Rounds

Trailer: Introducing NEJM AI Grand Rounds Podcast 1 min · 05 Dec 2022

All episodes from NEJM AI Grand Rounds →

Report any issue

Source

Recorded15 May 2024

Publisherai-podcast.nejm.org ↗

Handlerec:14725437

Show notes

In this episode of the NEJM AI Grand Rounds podcast, Dr. Nigam Shah, a distinguished Professor of Medicine at Stanford University and inaugural Chief Data Scientist for Stanford Health Care, shares his journey from training as a doctor in India to becoming a leading figure in biomedical informatics in the United States. He discusses the transformative impact of computational tools in understanding complex biological systems and the pivotal role of AI in advancing health care delivery, particularly in improving efficiency and addressing systemic challenges. Dr. Shah emphasizes the importance of real-world integration of AI into clinical settings, advocating for a balanced approach that considers both technological capabilities and the systemic considerations of AI in medicine. The conversation also explores the democratization of medical knowledge, why open-source models are under-researched in medicine, and the crucial role of data quality in training AI systems. Transcript.

Ask this episode

“What did the council decide on item 42?” — answered with the speaker and the moment.