NEJM AI Grand Rounds
- Folgen
- 48
- Erscheint
- monatlich
- Letzte Folge
- 21. Okt. 2026
Über den Podcast
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.
Folgen 48
Abridge’s Dr. Michal Nedoszytko on Physicians Who Build Software
Dr. Michał Nedoszytko, clinician scientist at Abridge and interventional cardiologist, has spent two decades building software alongside clinical practice. He explains how AI can help physicians gather better …
Shownotes
Dr. Michał Nedoszytko, clinician scientist at Abridge and interventional cardiologist, has spent two decades building software alongside clinical practice. He explains how AI can help physicians gather better information before an encounter, improve the quality of conversations with patients, and prototype solutions to problems that clinicians experience every day. Nedoszytko argues that medical training gives physicians lived knowledge that they can bring to building software. Yet he draws a firm distinction between making software and making software safe. In regulated clinical environments, engineers, privacy protections, and rigorous delivery remain indispensable. As AI assumes more analytical and administrative work, he hopes medicine becomes more grounded in its human purpose: clinicians closer to patients, present in the moment, rather than focused on screens and documentation.
Beyond the Hype: Dr. Xiao Liu on Evaluating Medical AI
The promise of medical AI is not simply better performance — it is better care grounded in evidence patients and clinicians can trust. Dr. Xiao Liu, a clinician and medical AI researcher affiliated with the …
Shownotes
The promise of medical AI is not simply better performance — it is better care grounded in evidence patients and clinicians can trust. Dr. Xiao Liu, a clinician and medical AI researcher affiliated with the University of Birmingham and Microsoft AI, has spent her career asking what rigorous evaluation should look like as new technologies move from publications into practice. She describes reporting guidelines as tools for transparency rather than prescriptions and explains why seeing product development from inside industry changed her understanding of implementation. Looking ahead, Liu imagines a medical profession in which readily available knowledge shifts physicians toward a more interpersonal role: accompanying patients through uncertainty, deterioration, treatment failure, recovery, and life-changing diagnoses. At the same time, she sees AI opening new scientific possibilities by revealing biomarkers, disease phenotypes, and treatment-response patterns that current medical categories may miss. The challenge is to preserve rigor without letting familiar methods prevent medicine from learning something genuinely new.
Dr. Suchi Saria on Building AI That Changes Care
A patient can deteriorate while the warning signs remain buried in a noisy electronic record. Dr. Suchi Saria, Founder and CEO of Bayesian Health and a faculty member at Johns Hopkins University, has spent her …
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A patient can deteriorate while the warning signs remain buried in a noisy electronic record. Dr. Suchi Saria, Founder and CEO of Bayesian Health and a faculty member at Johns Hopkins University, has spent her career trying to surface those signals sooner. She explains why a strong retrospective model is only the starting point — and why prospective validation, workflow integration, physician adoption, monitoring, and financial sustainability determine whether clinical AI ever reaches patients. Her work on early sepsis recognition became personal after she lost her nephew to the condition, turning an academic agenda into an urgent effort to prevent failures to rescue. Saria also challenges the current center of gravity in health care AI: tools increasingly prepare for visits, transcribe conversations, and support billing, while comparatively few directly help clinicians care for patients. She envisions a third modality of medicine alongside drugs and devices — rigorous, software-based interventions that identify when to act, what to do, and for whom.
Weave’s Brandon Rice on Rebuilding Drug Regulation with AI
Brandon Rice believes that improving health care sometimes means improving the systems behind it. Through his work at Weave, he focuses on modernizing the regulatory infrastructure that helps bring new …
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Brandon Rice believes that improving health care sometimes means improving the systems behind it. Through his work at Weave, he focuses on modernizing the regulatory infrastructure that helps bring new medicines to market. He discusses the challenge of organizing scientific knowledge, communicating with regulators, and navigating processes that can span more than a decade. His vision is that AI can reduce administrative burden while preserving the rigor required for patient safety and scientific progress.
OpenAI’s Karan Singal on HealthBench and the Future of Medical AI
Medical expertise has always been scarce. Dr. Karan Singal believes AI can help change that. Drawing on his work at OpenAI and earlier efforts behind Med‑PaLM, he discusses how clinicians and patients are …
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Medical expertise has always been scarce. Dr. Karan Singal believes AI can help change that. Drawing on his work at OpenAI and earlier efforts behind Med‑PaLM, he discusses how clinicians and patients are already using AI to answer questions, support decisions, and navigate care. He argues that the future of health AI is not only about improving model performance, but also about helping people advocate for themselves more effectively. Through HealthBench and ChatGPT for Clinicians, his team is exploring how to make these systems safer, more useful, and more trustworthy. The result is a vision of health care where expertise becomes more accessible without losing sight of clinical responsibility.
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 …
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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.
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 …
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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.
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 …
Shownotes
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.
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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 …
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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.
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 …
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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.
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 …
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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.
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 …
Shownotes
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.
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 …
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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.
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 …
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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.
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 …
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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.
Can AI Accelerate Science? Dr. Andy Beam on AI’s Next Frontier
Dr. Andy Beam has trained models, mentored scientists, and used data to quantify the value of treatments. In this episode of NEJM AI Grand Rounds, Raj Manrai turns the table on his co-host, reflecting on how …
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Dr. Andy Beam has trained models, mentored scientists, and used data to quantify the value of treatments. In this episode of NEJM AI Grand Rounds, Raj Manrai turns the table on his co-host, reflecting on how Andy’s childhood misdiagnosis, and the failure of human recall, revealed the diagnostic promise of machine learning. As a Harvard professor, he mentored hybrid thinkers and built tools to evaluate safety, not just performance. Now CTO of Lila Sciences, he’s building an experimental AI system to generate its own hypotheses and test them in the real world. This conversation is a front-row seat to the next evolution of science.
Google’s Efforts to Build Patient-Facing AI: A Conversation with Drs. Alan Karthikesalingam and Anil Palepu
In this episode of NEJM AI Grand Rounds, guests Drs. Alan Karthikesalingam and Anil Palepu of Google walk co-hosts Raj Manrai and Andy Beam through the making and evaluation of AMIE, an AI system designed to …
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In this episode of NEJM AI Grand Rounds, guests Drs. Alan Karthikesalingam and Anil Palepu of Google walk co-hosts Raj Manrai and Andy Beam through the making and evaluation of AMIE, an AI system designed to conduct clinical conversations with patients. Alan and Anil explain how AMIE was trained using synthetic doctor-patient interactions generated by LLMs playing multiple roles—doctor, patient, critic, and moderator. They reveal how synthetic dialogue, guided by structured feedback and grounded in search, proved more effective than noisy real-world transcripts in building a model that could reason, ask questions, and show empathy. The discussion also covers what the “long tail” of medicine demands for building robust AI systems and how AMIE might one day augment real clinical workflows. Finally, Alan reflects on how AI has changed—and how it hasn’t—in the two years since he was last on the podcast.
Rewriting the Clinical Playbook: Dr. Shiv Rao on Scaling Empathy with AI
Dr. Shiv Rao, cardiologist and CEO of Abridge, joins hosts Raj Manrai and Andy Beam on NEJM AI Grand Rounds for an inspiring conversation at the intersection of medicine, technology, and meaning. Shiv shares …
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Dr. Shiv Rao, cardiologist and CEO of Abridge, joins hosts Raj Manrai and Andy Beam on NEJM AI Grand Rounds for an inspiring conversation at the intersection of medicine, technology, and meaning. Shiv shares the origin story of Abridge, reflecting on how a deeply human encounter in clinic sparked the idea for a company now transforming clinical documentation across more than 100 health systems. From his early days programming electronic music to navigating LLM deployment at scale, Shiv offers a rare look into the soul of a founder building not just infrastructure — but a movement. He unpacks how generative AI can be used to restore presence in the clinic, what it takes to earn clinician trust, and why he believes taste, empathy, and curiosity are the real moats in health care AI.
Pixels to Protocols: Building the AI Future of Pathology with Dr. Faisal Mahmood
Dr. Faisal Mahmood, Associate Professor of Pathology at Brigham and Women’s Hospital and Harvard Medical School, joins hosts Raj Manrai and Andy Beam on NEJM AI Grand Rounds to explore the frontier of …
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Dr. Faisal Mahmood, Associate Professor of Pathology at Brigham and Women’s Hospital and Harvard Medical School, joins hosts Raj Manrai and Andy Beam on NEJM AI Grand Rounds to explore the frontier of computational pathology. From pioneering foundational models for whole slide imaging to commercializing a multimodal generative AI copilot for pathology, Faisal shares how his team is redefining what’s possible in digital diagnostics. He discusses the power of open-source culture in accelerating innovation, his lab’s FDA breakthrough designation, and how generative AI could trigger widespread digitization in pathology. Faisal also reflects on his creative approach to problem selection and offers a vision for a future shaped by patient-level foundation models and agent-led computational biology.
From Bedside to Boardroom: How AI, Multi-Omics, and New Business Models Are Shaping the Biomedical Frontier with Morgan Cheatham
Morgan Cheatham joins hosts Raj Manrai and Andy Beam on NEJM AI Grand Rounds to discuss the evolving landscape of artificial intelligence in health care, from its role in automating clinical documentation to …
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Morgan Cheatham joins hosts Raj Manrai and Andy Beam on NEJM AI Grand Rounds to discuss the evolving landscape of artificial intelligence in health care, from its role in automating clinical documentation to its transformative potential in genomic medicine. A venture capitalist and future physician, Morgan shares how his background in computational decision sciences led him to medical school and investing, offering insights into how AI is reshaping everything from disease phenotyping and clinical decision-making to scaling precision medicine. He reflects on his work evaluating ChatGPT’s performance on the USMLE, the growing importance of genomic learning health systems, and why the biggest challenge isn’t technological innovation—but aligning payment models to support AI-driven advancements in medicine.
From Clinical Notes to GPT-4: Dr. Emily Alsentzer on Natural Language Processing in Medicine
Dr. Emily Alsentzer joins hosts Raj Manrai and Andy Beam on NEJM AI Grand Rounds to discuss the evolution of natural language processing (NLP) in medicine. A Stanford faculty member and expert in clinical AI …
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Dr. Emily Alsentzer joins hosts Raj Manrai and Andy Beam on NEJM AI Grand Rounds to discuss the evolution of natural language processing (NLP) in medicine. A Stanford faculty member and expert in clinical AI, Emily shares her journey from pre-med to biomedical AI, the role of language models in medical decision-making, and the ethical considerations surrounding bias in AI. The conversation explores everything from the early days of rule-based NLP to the modern era of large language models, the challenges of evaluating AI in clinical settings, and what the future holds for open-source medical AI.
Health Care at the Breaking Point: Dr. Zak Kohane Returns to NEJM AI Grand Rounds
In this return appearance on NEJM AI Grand Rounds, Dr. Zak Kohane joins hosts Raj Manrai and Andy Beam to discuss the evolving landscape of AI in medicine. As the first repeat guest on the show, Dr. Kohane …
Shownotes
In this return appearance on NEJM AI Grand Rounds, Dr. Zak Kohane joins hosts Raj Manrai and Andy Beam to discuss the evolving landscape of AI in medicine. As the first repeat guest on the show, Dr. Kohane shares insights on health care system challenges, the Human Values Project, and his perspectives on the most significant AI developments of 2024. The conversation explores everything from the practical applications of AI in health care to philosophical discussions about machine psychology and the future of doctor-patient relationships.
The Economics of AI: A Conversation with Larry Summers
In this episode of NEJM AI Grand Rounds, hosts Raj Manrai and Andy Beam interview Larry Summers about artificial intelligence’s transformative potential and its implications for society. The conversation …
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In this episode of NEJM AI Grand Rounds, hosts Raj Manrai and Andy Beam interview Larry Summers about artificial intelligence’s transformative potential and its implications for society. The conversation explores Summers’ perspective on AI as potentially the most significant technology ever invented, his role on OpenAI’s board following the November 2023 leadership transition, and his thoughts on how AI will reshape economics and human society. The episode provides unique insights into AI’s development trajectory, the challenges of technological prediction, and the intersection of economics and artificial intelligence.
Partners in Diagnosis: ChatGPT, a Mother’s Intuition, and a Doctor’s Expertise with Courtney Hofmann and Dr. Holly Gilmer
In this episode of NEJM AI Grand Rounds, hosts Raj Manrai and Andy Beam interview Courtney Hofmann, a mother whose use of ChatGPT led to her son’s diagnosis of tethered cord syndrome after seeing 17 doctors …
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In this episode of NEJM AI Grand Rounds, hosts Raj Manrai and Andy Beam interview Courtney Hofmann, a mother whose use of ChatGPT led to her son’s diagnosis of tethered cord syndrome after seeing 17 doctors over three years, and Dr. Holly Gilmer, the pediatric neurosurgeon who confirmed and treated the condition. The conversation explores how AI helped bridge diagnostic gaps, systemic health care challenges that led to missed diagnoses, and the evolving role of AI in patient advocacy and medical practice. The episode highlights the importance of combining AI insights with human medical expertise, while discussing both the potential and limitations of AI in health care.
The Pulse of Progress: AI in Cardiology with Dr. David Ouyang
In this episode of NEJM AI Grand Rounds, hosts Raj Manrai and Andy Beam interview Dr. David Ouyang, a cardiologist and AI researcher at Cedars-Sinai Medical Center. The conversation explores Ouyang’s journey …
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In this episode of NEJM AI Grand Rounds, hosts Raj Manrai and Andy Beam interview Dr. David Ouyang, a cardiologist and AI researcher at Cedars-Sinai Medical Center. The conversation explores Ouyang’s journey from medical training to AI research and entrepreneurship, his groundbreaking work in applying AI to cardiology imaging, and the challenges of bringing AI innovations from academia to clinical practice. Ouyang discusses his experience conducting randomized controlled trials (RCTs) for AI algorithms in echocardiography, the process of commercializing research through Y Combinator, and the hurdles in reimbursement for AI-based medical devices. The episode also delves into the future of AI in cardiology, the importance of clinician involvement in AI development, and the potential impact of large language models (LLMs) on medical practice. Ouyang shares insights on balancing clinical value with business considerations in health care AI and offers advice for researchers looking to conduct clinical trials for AI technologies.
AI at the Frontlines: Dissecting Clalit’s Roadmap for the Future of Public Health with Noa Dagan and Ran Balicer
In this episode of NEJM AI Grand Rounds, hosts Raj Manrai and Andy Beam interview Dr. Noa Dagan and Dr. Ran Balicer from the Clalit Research Institute in Israel. The conversation explores Clalit’s …
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In this episode of NEJM AI Grand Rounds, hosts Raj Manrai and Andy Beam interview Dr. Noa Dagan and Dr. Ran Balicer from the Clalit Research Institute in Israel. The conversation explores Clalit’s groundbreaking work in implementing predictive models at the point of care, their contributions to COVID-19 research, and the potential of AI in revolutionizing public health. Dagan and Balicer discuss the unique data set spanning more than half of Israel’s population, their approach to integrating AI into clinical practice, and their vision for the future of data-driven health care.
From Petri Dishes to Pitch Decks: Cultivating Health Care’s AI Future with Vijay Pande
In this episode of NEJM AI Grand Rounds, hosts Raj Manrai and Andy Beam interview Dr. Vijay Pande, a general partner at Andreessen Horowitz (A16Z) where he leads investments in health care and life sciences …
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In this episode of NEJM AI Grand Rounds, hosts Raj Manrai and Andy Beam interview Dr. Vijay Pande, a general partner at Andreessen Horowitz (A16Z) where he leads investments in health care and life sciences. The conversation explores Pande’s journey from academia to venture capital, his views on the future of AI in health care and biomedicine, and insights into the investment landscape for biotech and health tech companies. Pande discusses the challenges and opportunities in integrating AI into medical practice, the potential for AI to democratize health care access, and his thoughts on the development of artificial general intelligence (AGI).
Love and Large Language Models: Voices of the Future with Dr. Rohaid Ali and Dr. Fatima Mirza
In this episode of NEJM AI Grand Rounds, hosts Raj Manrai and Andy Beam interview Dr. Rohaid Ali and Dr. Fatima Mirza, a married couple and chief residents at Brown University. The conversation explores their …
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In this episode of NEJM AI Grand Rounds, hosts Raj Manrai and Andy Beam interview Dr. Rohaid Ali and Dr. Fatima Mirza, a married couple and chief residents at Brown University. The conversation explores their innovative work applying AI to health care, focusing on two major projects:
- Using ChatGPT to simplify surgical consent forms, making them more accessible to patients. This initiative led to widespread adoption within their healthcare system and inspired similar changes in other medical documentation, and
- Collaborating with OpenAI's Voice Engine to help a young patient who lost her voice due to a brain tumor by creating a custom AI-generated voice based on a short audio sample. Ali and Mirza discuss the challenges and opportunities of integrating AI into medical practice, emphasizing responsible deployment and human oversight.
They share insights on balancing personal and professional collaboration as a married couple working on research together. The episode features a lighthearted “newlywed game” segment, testing how well the couple knows each other’s perspectives. It concludes with Ali and Mirza offering advice to early-career doctors interested in AI and sharing their vision for AI’s future in medicine, highlighting the importance of ensuring equitable access to these technologies and the need for thoughtful implementation by medical professionals.
AI and the Evolution of Medical Thought with Dr. Adam Rodman
In this episode of the AI Grand Rounds podcast, Dr. Adam Rodman shares his unique journey from a historian to a physician deeply interested in the intersection of medicine and artificial intelligence. He …
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In this episode of the AI Grand Rounds podcast, Dr. Adam Rodman shares his unique journey from a historian to a physician deeply interested in the intersection of medicine and artificial intelligence. He highlights his unconventional path, driven by an obsession with epistemology and nosology, and his early exposure to AI through historical references and personal experiences with language models. Rodman discusses the evolution of clinical reasoning, the importance of probabilistic models, the implications of AI in diagnostic processes, and details his work with large language models like GPT-4. He also reflects on the balance between the benefits and challenges of AI in medicine, emphasizing the necessity of collaboration between computer scientists and medical professionals. Throughout the episode, Rodman underscores the potential of AI to re-humanize medicine while cautioning against misapplications of the technology.
Translational AI in Medicine: Unlocking AI’s Potential in Health Care with Nigam Shah
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 …
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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.
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