JAMA+ AI Conversations

JAMA Network

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. Join us to uncover what lies ahead at the intersection of AI and medicine.

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September 10 · 23 min
From Aging to AI and Beyond: A Conversation With Eric Topol
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
August 27 · 22 min
ADVOCATing for Patients With Heart Failure
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 Failure FDA Perspective on the Regulation of Artificial Intelligence in Health Care and Biomedicine
August 13 · 19 min
Enriching Clinical Trials With Machine Learning
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
July 30 · 22 min
From the JAMA Network: Acoustic Analysis of Primary Care Patient–Clinician Conversations to Screen for Cognitive Impairment
Interview with Joseph T. Colonel, PhD, author Acoustic Analysis of Primary Care Patient–Clinician Conversations to Screen for Cognitive Impairment. Hosted by Cynthia E. Armand, MD. Related Content: Acoustic Analysis of Primary Care Patient–Clinician Conversations to Screen for Cognitive Impairment
July 16 · 41 min
From the JAMA Network: AI Scribes Are Here, but Is Health Care Ready?
The rise in use and function of ambient AI scribes is arguably one of the fastest technologic changes ever seen in health care. In this episode of Healthy Dialogue, host Derek Angus, MD, MPH, is joined by Vincent Liu, MD, MS, Chief Data Officer of The Permanente Medical Group in Kaiser Permanente, to discuss the rapidly changing world of ambient AI. Related Content: Ambient AI Scribes and the Quintuple Aim Changes in Clinician Time Expenditure and Visit Quantity With Adoption of Artificial Intelligence–Powered Scribes AI Scribes Are Here, but Is Health Care Ready?
July 1 · 21 min
From Silicon Valley to the Vatican: The Expanding Debate on AI Ethics
In this episode of JAMA+ AI Conversations, Roy Perlis, MD, MSc, and Yulin Hswen, ScD, MPH, discuss Anthropic's participation in the Vatican presentation of Pope Leo XIV's AI encyclical, Magnifica Humanitas. The conversation explores AI ethics, interpretability, governance, AI safety, and the growing role of health care, public health, and global institutions in shaping the future of AI. Related Content: From Silicon Valley to the Vatican—The Expanding Debate on AI Ethics
June 17 · 19 min
The Wizard of Oz in Medical AI
Is it enough for AI to be accurate, or are we mistaking performance for impact? Does AI change clinician behavior, improve patient decisions, or simply create a convincing performance of intelligence? Yun Liu, PhD, research scientist at Google Research, speaks with JAMA+ AI Associate Editor Yulin Hswen, ScD, MPH, about what is behind the curtain in these AI systems. Related Content: The Wizard of Oz in Medical AI
June 4 · 20 min
Teaching AI to Read Patient Histories
Every patient has a story, but in modern health care that story is buried across thousands of notes, lab results, and fragmented records. Nigam H. Shah, MBBS, PhD, of Stanford University Department of Medicine joins JAMA Associate Editor Yulin Hswen, ScD, MPH, to explore how researchers are building AI systems that can read and understand a patient's full medical history in seconds. Related Content: Chatting With AI and the Electronic Health Record
May 21 · 16 min
Designing Trustworthy Clinical AI
Join JAMA+ AI Associate Editor Yulin Hswen, ScD, MPH, for a conversation about the practical implementation of trustworthy clinical AI. Guests Emily Tat, MD, and Peter Brodeur, MD, discuss ARISE, a research network focused on the real-world effects of AI on clinical care. Related Content: Designing Trustworthy Clinical AI
May 7 · 25 min
AI at the Policy Table
As artificial intelligence increasingly shapes population health decisions, evidence and accuracy matter. In this episode of JAMA+ AI Conversations, Associate Editor Yulin Hswen, ScD, MPH, speaks with Sandro Galea, MD, MPH, DrPH, Editor of JAMA Health Forum, about how AI is entering health policy, when it is ready for use, and what rigorous, policy-focused AI research is most needed. Related Content: AI at the Policy Table
April 23 · 19 min
AI Drug Safety in Pregnancy
Why can signals that appear consistent across many studies still reflect shared bias; how do sibling comparisons help recalibrate cumulative evidence; and what AI-enabled approaches can add to large-scale evidence integration? Viktor H. Ahlqvist, PhD, from the Karolinska Institute joins JAMA and JAMA+ AI Associate Editor Yulin Hswen, ScD, MPH, to discuss why automated drug safety surveillance during pregnancy is urgently needed and how AI and computation can strengthen or undermine causal inference. Related Content: AI Drug Safety in Pregnancy
April 9 · 20 min
Understanding Disease Trajectories With AI
How might AI amplify epidemiological insight into neurodegenerative and systemic disease? JAMA+ AI Associate Editor Yulin Hswen, ScD, MPH, speaks with Fang Fang, MD, PhD, professor at Karolinska Institutet and head of the Integrative Epidemiology group. Drawing on Fang Fang's work in ALS, Parkinson disease, dementia, energy metabolism, immune modulation, and gut microbiome interactions, their conversation probes how AI methods might help map disease trajectories, identify prognostic markers, and ultimately support precision prevention and translational research, while preserving scientific rigor and interpretability. Related Content: AI and the Epidemiology of Complex Disease
March 26 · 24 min
AI Chatbots and Youth Mental Health
What are the safety, evidence standards, and transparency needed for AI chatbots used in mental health contexts, particularly for young people. John Torous, MD, MBI, JAMA Psychiatry Author Interviews podcast host, joins JAMA+ AI Associate Editor Yulin Hswen, ScD, to discuss risks, data protections, and the clinical safeguards required to ensure responsible use. Related Content: AI Chatbots and Youth Mental Health
March 12 · 24 min
Leaping Forward Into… What? An Interview With Dr Robert Wachter
Dr Robert Wachter, chair of the Department of Medicine at UC San Francisco, speaks with JAMA+ AI Editor in Chief Roy Perlis about his new book, "A Giant Leap." Their discussion addresses multiple potential impacts of AI in medicine in terms of clinical practice but also training the next generation of clinicians. Related Content: Leaping Forward Into…What?—An Interview With Robert M. Wachter
February 26 · 23 min
AI and "Do No Harm"
In this episode, JAMA+ AI Associate Editor Yulin Hswen, ScD, MPH, speaks with David Wu, MD, PhD, and Adam Rodman, MD, MPH, about what safe clinical use of LLMs requires. Drawing on the framework of Do No Harm, they examine failure modes, limits of accuracy-based evaluation, clinician AI interaction, and safeguards needed as medical AI moves into patient care. Related Content: From AI Bench to AI Bedside
February 12 · 18 min
Stumbling Toward AI in the Clinic
In this episode of JAMA+ AI Conversations, Editor in Chief Roy Perlis and Associate Editor Yulin Hswen debate recent articles highlighted in JAMA+ AI, including work on patient messaging and suicide screening, plus a call for more critical thinking in medicine. Related Content: Stumbling Toward AI in the Clinic
January 29 · 12 min
Chatting With a Chatbot: The History of the First Clinical Chatbots, Straight From an LLM
A large language model (LLM) details the history of 2 early chatbots, ELIZA and PARRY, in conversation with JAMA+ AI Editor in Chief Roy Perlis. This podcast was recorded using OpenAI's ChatGPT in voice mode, via web interface, running on GPT-4o. Related Content: What Can 50-Year-Old Chatbots Teach Us About Clinical Applications of AI?
January 15 · 21 min
Seeing Health Through the Eye and AI
Retinal images are becoming powerful windows into human health. Cecilia Lee, MD, MS, joins JAMA and JAMA+ AI Associate Editor Yulin Hswen to explore how AI-enhanced imaging reveals early disease signals, leverages large datasets, and shifts clinical practice in ophthalmology. Related Content: Insights From the Eye With AI
Dec 30, 2025 · 17 min
Multiple Reasoning Models and the Future of AI Chatbots
AI chatbots have advanced rapidly, incorporating new reasoning architectures that reshape decision-making and medical education. Jonathan Chen, MD, PhD, and Ethan Goh, MD, MS, of Stanford University join JAMA and JAMA+ AI Associate Editor Yulin Hswen, ScD, MPH, to discuss the latest generation of AI models, the importance of evaluating benefits and harms, and sycophancy in AI systems. Related Content: Multiple Reasoning Models and the Future of AI Chatbots AI Chatbots in Clinical Practice Large Language Model Influence on Diagnostic Reasoning
Dec 18, 2025 · 19 min
Discussing the Latest Research in AI and Health
JAMA+ AI Editor in Chief Roy Perlis and Associate Editor Yulin Hswen discuss some of the most cited AI papers in 2025 across the JAMA Network. A little bit of gen AI, some prediction models, and deep learning from videos as well as an increasing awareness of the challenges of real-world deployment. Related Content: AI and Health—The Year in Review

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