NEJM AI Grand Rounds

Hosted by NEJM Group

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May 2026

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About the show

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.

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43 recent

May 20, 2026Episode 421 hr 5 min

The OpenEvidence Episode: Dr. Travis Zack on the Future of Clinical Evidence

Dr. Travis Zack, Chief Medical Officer of OpenEvidence, takes us behind the scenes of the start and growth of the company, and brings a clinician’s perspective to one of medicine’s hardest questions: how should artificial intelligence support decision-making? In this episode, he emphasizes that reasoning—not just correctness—defines good care, and that evidence must be contextual, accessible, and usable. He explores how physicians use AI to reduce uncertainty, why global constraints challenge the idea of a single “right answer,” and how trust depends on transparent use of medical literature. For clinicians navigating complex decisions, this conversation highlights both the promise and the limits of AI—and the enduring importance of human judgment. Transcript.

April 15, 2026Episode 4151 min

Doctronic’s Autonomous AI with Dr. Byron Crowe

Doctronic CMO Dr. Byron Crowe 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.

March 18, 2026Episode 401 hr 7 min

AI’s Next Frontier with Dr. Kyunghyun Cho

Dr. Kyunghyun Cho 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.

February 18, 2026Episode 3953 min

Epic’s Approach to AI with Seth Hain

Clinical AI only helps patients if clinicians and health systems trust it. Seth Hain describes how Epic is building foundation models that respect institutional autonomy, minimize burden, and prioritize safety. He discusses scaling laws in structured medical data, cautious deployment for clinical interventions, and why understanding causality—not just correlation—is essential. This conversation reframes AI not as disruption, but as infrastructure for safer, more reliable care. Transcript.

January 21, 2026Episode 3854 min

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

For Dr. 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.

December 17, 2025Episode 371 hr 18 min

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

For Dr. Zak 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.

November 19, 2025Episode 3638 min

From Hindsight Bias to Machine Bias: Dr. Laura Zwaan on Learning from Mistakes

As a cognitive psychologist, Dr. Laura Zwaan studies how humans make—and learn from—mistakes. In this episode of NEJM AI Grand Rounds, she brings that lens to AI, showing how machines inherit our biases and why both need transparency and reflection. From the challenge of defining diagnostic error to the promise of “machine psychology,” Dr. Zwaan explores how human reasoning can inform safer algorithms and better care. Her message is clear: the path to trustworthy AI begins with understanding ourselves. Transcript.

October 15, 2025Episode 3548 min

Medicine, Machines, and Magic: Dr. Jonathan Chen on Medical AI

In this episode, Dr. Jonathan Chen joins the hosts to discuss his path from teenage programmer to Stanford physician-informatician and why machine learning has both thrilled and unnerved him. From his 2017 NEJM essay warning about “inflated expectations” to his latest studies showing GPT‑4 outperforming doctors on diagnostic tasks, Dr. Chen describes a discipline learning humility at machine speed. This conversation spans medical education, automation anxiety, magic, and why empathy—not memorization—may become the most valuable clinical skill. Transcript.

September 17, 2025Episode 341 hr 2 min

From Clinician to Chief Health AI Officer: A Conversation with Dr. Karandeep Singh

Dr. Karandeep Singh brings two worlds together: programming and medicine. In this conversation, he explains how early experiments with code led him to biomedical informatics, why gaps between paper performance and clinical reality must be confronted, and how governance committees weigh ethics and safety. Now serving as Chief Health AI Officer at UC San Diego Health, he reflects on lessons from deploying sepsis prediction tools, the risks of hype, and the promise of integration. For clinicians, Singh’s story is a reminder that the best AI is guided by patient care, deep expertise, and humility about the limits of technology. Transcript.

August 20, 2025Episode 3342 min

Radiologist Turned CEO: Dr. Jeremy Friese on AI for Prior Authorization

Dr. Jeremy Friese knows medicine from both sides. A practicing radiologist and technology executive, he’s seen firsthand how administrative burden undermines care. In this episode of NEJM AI Grand Rounds, he walks through the origins of prior authorization, explains why he believes artificial intelligence can close the gap between patients and payers, and argues that real reform means showing your work—just like in math class. At Humata, he’s combining human oversight, LLMs, and interoperability to try to fix a broken system. For clinicians overwhelmed by back-office complexity, this conversation offers both urgency and optimism. Transcript.