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.
Episodes
Wednesday May 15, 2024
Translational AI in Medicine: Unlocking AI’s Potential in Health Care with Nigam Shah
Wednesday May 15, 2024
Wednesday May 15, 2024
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.
Wednesday Apr 17, 2024
From Theory to Therapy: The Evolution of AI in Medicine with Dr. Daphne Koller
Wednesday Apr 17, 2024
Wednesday Apr 17, 2024
In this episode of the AI Grand Rounds podcast, Dr. Daphne Koller charts her professional trajectory, tracing her early fascination with computers to her influential role in AI and health care. Initially intrigued by the capacity of computers for decision-making based on theoretical principles, Koller witnessed her niche area — once considered peripheral to AI — grow to dominate the field. Her curiosity led her from abstract theory to practical machine learning applications and eventually to the complex world of biomedicine. Throughout the podcast, Koller shares her shift from pure computer science to the integration of machine learning in biological and medical research. She explains the unique challenges of applying AI to biology, distinguishing it from more deterministic fields, and how these complexities feed into her work at insitro, where she is leveraging AI throughout the drug discovery and development process, from disease understanding to therapeutic application and monitoring. She advocates for the democratizing potential of AI, underscoring its capacity to enable broader participation in scientific inquiry and problem-solving.
Transcript.
Wednesday Mar 20, 2024
Wednesday Mar 20, 2024
In this episode of the AI Grand Rounds podcast, Dr. Eric Horvitz describes his career evolution from an interest in neurobiology to significant contributions in AI, particularly in understanding complex systems and applying AI in medicine. He discusses the shift from studying neurobiology to embracing AI and computational methods as tools for unraveling the complexities of the human mind and broader decision-making processes. Horvitz emphasizes the importance of probabilistic models and decision theory in AI, highlighting his work on bounded rationality and the challenges of interpretability in AI systems. He also reflects on the potential of AI in medicine, the necessity of responsible AI development, and the future of AI research. He suggests a blend of excitement and caution as AI technologies become increasingly integrated into various aspects of human life and decision making.
Transcript.
Wednesday Feb 21, 2024
AI Frontiers with James Zou: The Future of Multi-Modal AI in Medicine
Wednesday Feb 21, 2024
Wednesday Feb 21, 2024
In this episode of the AI Grand Rounds podcast, Dr. James Zou shares his personal journey to discovering machine learning during his graduate studies at Harvard. Fascinated by the potential of AI and its application to genomics and medicine, Dr. Zou embarked on a journey that took him from journalism to the forefront of AI research. He has been instrumental at Stanford in translating machine learning advancements into clinical settings, particularly through genomics. The discussion also delves into the unique use of social media for gathering medical data, showcasing an innovative approach to AI model training with real-world medical discussions. Dr. Zou touches on the ethical implications of AI, the importance of responsible AI development, and the potential of language models like GPT-4 in medicine, despite the challenges of model drift and alignment with human preferences.
Transcript.
Wednesday Jan 17, 2024
Interrogating AI Fairness and Bias in Dermatology and Beyond with Dr. Roxana Daneshjou
Wednesday Jan 17, 2024
Wednesday Jan 17, 2024
In this episode of the AI Grand Rounds podcast, Dr. Roxana Daneshjou shares her journey from a childhood influenced by early exposure to science to her current role as an assistant professor at Stanford. Her path includes a critical shift during medical school, where her interest in computational methods and human genomics led her to pursue both an M.D. and a Ph.D. Her specialization in dermatology was driven by its visual nature and the opportunity to form long-term relationships with patients. Dr. Daneshjou emphasizes the importance of AI in addressing fairness and bias in dermatology, discussing her research on disparities in AI performance across diverse skin tones. The podcast also delves into broader issues of AI in health care, discussing the potential and challenges of integrating large language models into medical practice, and highlighting the need for interdisciplinary collaboration between clinicians and computer scientists in AI development. Dr. Daneshjou’s optimism for the future centers on the new generation of medical professionals who are increasingly concerned about fairness and equity in AI.
Transcript.
Tuesday Jan 02, 2024
Medicine as a Knowledge Processing Discipline with Dr. Zak Kohane
Tuesday Jan 02, 2024
Tuesday Jan 02, 2024
In this episode, Dr. Zak Kohane shares his journey into AI and medicine, reflecting on early influences from science fiction authors and programming experiences in his youth. He discusses his academic path, moving from programming and machine instruction to medical school, driven partly by practical advice and personal ambition. Kohane highlights his realization during medical school that medicine was not as scientifically advanced as he expected, motivating his interest in improving medical decision-making through AI. He recalls his time at MIT, contrasting the intellectual freedom there with today’s academic environment, and reflects on the impact of large language models in medicine, emphasizing their real-world applications and potential to transform medical practice. Kohane also discusses the importance of mentorship, his approach to nurturing talent, and the role of his department at Harvard in advancing the field of biomedical informatics. Finally, he shares insights on the NEJM AI journal, its objectives, and the challenges and opportunities in medical AI today.
Transcript.
Wednesday Nov 29, 2023
Wednesday Nov 29, 2023
In this episode, Dr. Judy Wawira Gichoya, Associate Professor in the Department of Radiology and Imaging Sciences at Emory University School of Medicine, details her journey from Kenya to the United States, from interventional radiology to artificial intelligence.
Transcript.
Wednesday Oct 25, 2023
Machines & Genes: The Future of AI in Biology with Dr. George Church
Wednesday Oct 25, 2023
Wednesday Oct 25, 2023
In this episode, vanguard geneticist Dr. George Church recounts his storied career from his early fascination with computers and science to his pioneering work in genomics and synthetic biology. Dr. Church developed innovative DNA sequencing methods that enabled the first sequencing of the human genome. He was also instrumental in developing CRISPR gene editing technology. Dr. Church discusses his controversial ideas around resurrecting wooly mammoths and using genome sequencing in dating apps to prevent genetic diseases. He also provides insights into founding genomics companies and the role of AI in advancing biotechnology. As a professor of genetics at Harvard Medical School and the founder of multiple genomics companies, Dr. Church emphasizes the potential for synthetic biology and genetics to transform medicine and society.
Transcript.
Wednesday Sep 27, 2023
Mark Cuban on AI, Trust in Health Care, and Skip Bayless
Wednesday Sep 27, 2023
Wednesday Sep 27, 2023
In this episode, we’re joined by business magnate and investor Mark Cuban. Cuban describes his journey from humble beginnings as a self-taught programmer to becoming a successful serial entrepreneur and owner of an NBA team. Cuban shares the founding story of his pharmacy benefits company, Cost Plus Drugs, and his vision for reimagining the reimbursement system for care. He also articulates why he believes AI will be more transformative than prior technology shifts such as mobile and the internet and unpacks the potential of AI in addressing previously intractable problems in healthcare. Cuban is a self-made billionaire, bestselling author, star of Shark Tank, and owner of the Dallas Mavericks.
Transcript
Wednesday Aug 23, 2023
An Iron Fist in a Velvet Glove: A Conversation with Dr. Atul Butte
Wednesday Aug 23, 2023
Wednesday Aug 23, 2023
In this episode, pioneering informatician Dr. Atul Butte guides listeners through his storied career, from his early days as a pediatric endocrinologist and informatician in Boston to his trailblazing work on the West Coast. Dr. Butte describes his trailblazing efforts to both harness large-scale public biomedical data and share patient data across the entire UC Health System. Dr. Butte also discusses his entrepreneurial journey, including the genesis and vision behind companies like NuMedii. Dr. Butte is the Priscilla Chan and Mark Zuckerberg Distinguished Professor at UCSF and the Chief Data Scientist of the UC Health System.
Transcript

NEJM AI Grand Rounds
Artificial intelligence has transformed our consumer lives. And it's being increasingly applied to medicine. Medicine presents unique, technical, ethical, and legal questions around both the development and the sustainable deployment of AI. NEJM AI Grand Rounds, a podcast from NEJM Group, explores these topics while providing a forum to discuss evidence and resource sharing alongside debate about the best approaches to integrating AI within the healthcare system. NEJM AI, a new journal in medical artificial intelligence and machine learning, is coming soon from NEJM Group.

Andrew Beam, PhD, is a co-host of the NEJM Group podcast NEJM AI Grand Rounds. Andrew is a longtime AI optimist and is deeply committed to realizing an AI-enabled health care system that works for everyone. Andrew is an assistant professor in the Department of Epidemiology at the Harvard T.H. Chan School of Public Health, with a secondary appointment in the Department of Biomedical Informatics at Harvard Medical School. His lab develops new artificial intelligence methods by combining large-scale deep-learning models with techniques from causal inference to improve the safety and robustness for medical applications. He has a particular interest in using AI to improve neonatal and perinatal outcomes. Outside of the lab, Andrew lives in Waltham, MA, with his wife, Kristyn, a neonatologist and frequent collaborator. They are currently focused on training their largest neural net to date: a three-year-old named Hallie whose entropy maximization algorithm means there is never a shortage of things to clean up!

Arjun “Raj” Manrai, PhD, is a co-host of the NEJM Group podcast NEJM AI Grand Rounds. Raj is an assistant professor in the Department of Biomedical Informatics at Harvard Medical School, where he directs a research lab that works broadly on machine learning and statistical approaches to improve medical decision-making. Focus areas for his group include the clinical use of genomic data and blood laboratory biomarkers, inherited heart disease and kidney disease, decision-making across populations, and reproducibility challenges for medical AI. Raj took the scenic route to medical AI, earning an AB in physics from Harvard College, followed by a PhD in bioinformatics and integrative genomics from the Harvard-MIT Division of Health Sciences and Technology. He resides in the Boston area, and outside work he can usually be found losing home dance competitions to his two young daughters.
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