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JAMA+ AI Conversations

Discover the future of medicine with JAMA+ AI Conversations. This collection of interviews with clinicians, researchers, and AI experts explores how AI is impacting medicine – from clinical practice to training and research.

Podcast · By JAMA Network · English · Official site

Indexed episodes, last 90 days
3
Latest publication
Sep 10, 2026
Audience
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Earliest in this view
Aug 13, 2026

Latest episodes

  1. Episode · Sep 10, 2026

    From Aging to AI and Beyond: A Conversation With Eric Topol (opens the original)

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    In this episode of JAMA+ AI Conversations, Roy Perlis, MD, MSc, and Eric Topol, MD, move from the science of aging to how to think about AI-enabled medicine. Topol discusses what it will take for AI to move medicine from reactive to predictive, why some well-validated imaging AI remains underused while large language models have spread rapidly, and whether AI is actually giving clinicians more time with patients. Related Content: From Aging to AI and Beyond

  2. Episode · Aug 27, 2026

    ADVOCATing for Patients With Heart Failure (opens the original)

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    In this episode of JAMA+ AI Conversations, Roy Perlis, MD, MSc, and Haider Warraich, MD, sort out the prospects for AI-driven heart failure care that doesn't entail a human in the loop. Warraich is a program manager at ARPA-H, the Advanced Research Projects Agency for Health, responsible for ADVOCATE, an effort to support the development of AI to guide heart failure treatment, seeking to create AI agents that can pass muster with the FDA. Related Content: ADVOCATing for Patients With Heart Failu

  3. Episode · Aug 13, 2026

    Enriching Clinical Trials With Machine Learning (opens the original)

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    In this episode of JAMA+ AI Conversations, Roy Perlis, MD, MSc, and Joseph Geraci, PhD, of Queen's University discuss using machine learning to analyze clinical trials and related FDA interactions. Geraci's work focuses on identifying subpopulations with different responses to help plan and analyze future trials. Related Content: Enriching Clinical Trials With Machine Learning

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