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NEJM AI Grand Rounds

Podcast af NEJM Group

engelsk

Videnskab & teknologi

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Læs mere NEJM AI Grand Rounds

NEJM AI Grand Rounds, hosted by Arjun (Raj) Manrai, Ph.D. and Andrew Beam, Ph.D., features informal conversations with a variety of unique experts exploring the deep issues at the intersection of artificial intelligence, machine learning, and medicine. You’ll learn how AI will change clinical practice and healthcare, how it will impact the patient experience, and about the people who are pushing for innovation. Whether you are an AI researcher or a practicing clinician, these conversations will enlighten and surprise you as we journey through this very exciting field. Produced by NEJM Group.

Alle episoder

42 episoder

episode Doctronic’s Autonomous AI with Dr. Byron Crowe cover

Doctronic’s Autonomous AI with Dr. Byron Crowe

Doctronic CMO Dr. Byron Crowe [https://mcdn.podbean.com/mf/web/xsz4vhedu2s4fpyn/ByronCrowebio.pdf] describes how administrative complexity can interfere with timely, effective treatment, and how AI may help address those challenges. Crowe discusses Doctronic’s use of autonomous AI to renew prescriptions, arguing that this application can streamline care while maintaining clinical oversight. For physicians, this shift raises important questions about workflow, responsibility, and patient engagement. Crowe emphasizes that the goal is not automation for its own sake, but more reliable and accessible care. As these tools evolve, their impact will depend on how thoughtfully they are integrated into clinical practice. Transcript. [https://mcdn.podbean.com/mf/web/9nue7iu8y5fwgktb/Episode_41_Crowe.pdf]

15. apr. 2026 - 51 min
episode AI’s Next Frontier with Dr. Kyunghyun Cho cover

AI’s Next Frontier with Dr. Kyunghyun Cho

Dr. Kyunghyun Cho [https://kyunghyuncho.me/] is a leading AI researcher best known for co-authoring a landmark 2014 paper that introduced neural machine translation. In this episode, he discusses his wide-ranging career spanning fundamental AI research, co-founding Prescient Design (acquired by Genentech), and driving applications of AI in health care. For clinicians, Cho’s core message is pragmatic: AI should help health care run better. After years of work at NYU Langone, he reframed AI in medicine from solving rare diagnostic puzzles to improving operational prediction at scale. Cho emphasizes purpose‑built data, careful fine‑tuning, and regulatory accountability. His perspective connects technical rigor with system stewardship—and insists that patient voices must be present in AI governance. Transcript.  [https://mcdn.podbean.com/mf/web/ij6rxt9prfdu6y4u/Episode_40_Cho.pdf]

18. mar. 2026 - 1 h 7 min
episode Bridging AI and Biology to Tackle Medicine’s Hardest Problems with Dr. Marinka Zitnik cover

Bridging AI and Biology to Tackle Medicine’s Hardest Problems with Dr. Marinka Zitnik

For Dr. Marinka Zitnik [https://dbmi.hms.harvard.edu/people/marinka-zitnik], the promise of AI in medicine begins with acknowledging the scale of the problem. Most patients with rare diseases have no approved treatments, and traditional drug development timelines make progress painfully slow. In this conversation, she describes how AI-driven drug repurposing offers a way to work within existing constraints while still opening new therapeutic possibilities. She also highlights a structural issue that has limited impact: machine learning and biology communities often work in parallel, not together. By building shared benchmarks and collaborative spaces, Marinka argues, researchers can focus models on problems that truly matter for patients. The episode introduces her definition of AI agents as systems that can take actions and learn from outcomes — a capability she sees as essential for scientific discovery beyond static prediction. Throughout the discussion, Marinka returns to the value of academic freedom: the ability to chase difficult questions that require long time horizons and interdisciplinary thinking. Transcript. [https://mcdn.podbean.com/mf/web/n3xr5kytcb6h9acx/Episode_38_Zitnik.pdf]

21. jan. 2026 - 54 min
episode What Values are in AI? A Conversation with Dr. Zak Kohane cover

What Values are in AI? A Conversation with Dr. Zak Kohane

For Dr. Zak Kohane [https://dbmi.hms.harvard.edu/people/isaac-kohane], this year’s advances in AI weren’t abstract. They were personal, practical, and deeply tied to care. After decades studying clinical data and diagnostic uncertainty, he finds himself building his own EHR, reviewing his child’s imaging with AI, and re-thinking the balance between incidental and missed findings. Across each story is the same insight: clinicians and machines make mistakes for different reasons — and understanding those differences is essential for safe deployment. In this episode, Zak also highlights where AI is spreading fastest, and why: reimbursement. While dermatology and radiology aren’t broadly using AI for interpretation, revenue-cycle optimization is advancing rapidly. Meanwhile, ambient documentation has exploded — not because it increases accuracy or throughput, but because it improves clinician satisfaction in strained systems. Yet the most profound theme, he argues, is values. Models already show implicit preferences: some conservative, some aggressive. And unlike human clinicians, no regulatory framework examines how those preferences form. Zak calls for a new form of oversight that centers patients, recognizes bias, and bridges clinical expertise with technical transparency. Transcript. [https://mcdn.podbean.com/mf/web/g5sp9iv6tqwau7xv/Episode_37_Kohane.pdf]

17. dec. 2025 - 1 h 18 min
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