Claim OwnershipJAMA+ AI Conversations
Subscribed: 24Played: 327
Subscribe
Copyright © 2024 American Medical Association. All Rights Reserved.
Description
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.
59 Episodes
Reverse
How can AI systems reason safely in the open world of medicine? JAMA+ AI Associate Editor Yulin Hswen, ScD, MPH, talks with Eric Horvitz, MD, PhD, Chief Scientific Officer at Microsoft, about the future of AI in 5 years to 100 years, from neurons to the nebulous, and how we can guide AI to be copilots while maintaining integrity and safety in the clinical arena. Related Content: AI—Days of Future Past
Will AI usher in a new era of rapid drug discovery? In this episode of JAMA+ AI Conversations, Editor in Chief Roy Perlis interviews Ajamete Kaykas, Chief eXploration Officer at Insitro, a biotech company looking to apply AI to develop new therapeutics. Related Content: AI in the Lab—Will It Really Change Drug Discovery?
Derek Angus, MD, MPH, joins JAMA+ AI Editor in Chief Roy Perlis, MD, MSc, to discuss a special communication from JAMA Summit: Artificial Intelligence. Related Content: What the Experts Think About Where AI Is Headed AI, Health, and Health Care Today and Tomorrow
How will 2026 shape the world of AI in health? Editor in Chief Roy Perlis and Associate Editor Yulin Hswen discuss in this special episode marking one year since the launch of JAMA+ AI. Hosted by Roy H. Perlis, MD, MSc and Yulin Hswen, ScD, MPH. Related Content: What Will Next Year Bring for AI in Health? Detection of Epileptogenic Focal Cortical Dysplasia Using Graph Neural Networks Evaluating a Large Language Model in Translating Patient Instructions to Spanish Using a Standardized Framework Public Perception of Physicians Who Use Artificial Intelligence Assessment of Machine Learning to Estimate the Individual Treatment Effect of Corticosteroids in Septic Shock Artificial Intelligence Across the JAMA Network Early Warning Scores With and Without Artificial Intelligence Artificial Intelligence and Radiologist Burnout Complete AI-Enabled Echocardiography Interpretation With Multitask Deep Learning How AI Could Reshape Health Care—Rise in Direct-to-Consumer Models Artificial Intelligence–Enabled Wearable Devices and Nocturnal Scratching in Mild Atopic Dermatitis
How is Google Search evolving with AI and how do we ensure that language models maintain safety? JAMA+ AI Editor in Chief Roy Perlis, MD, talks with Michael Howell, MD, chief health officer at Google, about how he aims to balance innovation and safety in AI-driven medicine, building on his own work in hospital-based quality and safety. Related Content: "15% of Searches Have Never Been Typed Before" Three Epochs of Artificial Intelligence in Health Care
In this special edition of JAMA+ AI Conversations, editor in chief Roy Perlis is joined by Linda Brubaker, editor in chief of JAMA+ Women's Health and deputy editor at JAMA. They speak with Linda Moy, inaugural vice chair of AI for the NYU Department of Radiology and former editor of Radiology, about the opportunities and risks of applying AI in medical imaging. Will these new tools be a net positive for women's health? Related Content: The Promise and Challenge of AI for Women's Health
Michelle Mello, JD, PhD, MPhil, professor of law and health policy at Stanford University, joins JAMA+ AI Editor in Chief Roy Perlis, MD, MSc, to discuss her recently published JAMA Perspective that lays out a framework for when and how health care organizations should disclose AI use to patients. Dr Mello shares insights on the importance of patient trust and surveys that suggest many patients currently mistrust the use of AI in their care. Related Content: Ethical Obligations to Inform Patients About Use of AI Tools AI Disclosure and Patient Consent in Health Care
In this episode of JAMA+ AI Conversations, Microsoft CMO David Rhew, MD, discusses his journey from clinical practice to technology leadership, rapid progress in AI, its potential impacts on health care, and the challenges and opportunities that lie ahead for clinicians and researchers. Related Content: Changing Opinions About AI in Health Care
In this follow-up to a 2017 interview with JAMA Medical News, the University of Southern California's Maja Matarić, PhD, the computer scientist who pioneered the field of socially assistive robotics, discusses how artificial intelligence is advancing the field in areas ranging from autism to physical rehabilitation to anxiety and depression. Related Content: Social Robots That Help Support People's Health Are Getting a Boost From AI Socially Assistive Robots
3D total-body photography is used to detect lesions and melanoma in patients at high risk of developing skin cancer. The cost-effectiveness of this technology was examined in a recent study published in JAMA Dermatology. Roy Perlis, Editor in Chief of JAMA+ AI, joins economist Daniel Lindsay, PhD, to discuss the clinical and economic outcomes of this recent study. Related Content: Cost-Effectiveness Analysis of 3D Total-Body Photography for People at High Risk of Melanoma Can AI Improve the Cost-Effectiveness of 3D Total-Body Photography?
Despite recommendations from health care professionals, most patients with asthma do not track their symptoms, leaving limited data to help them discuss care options with their clinicians. JAMA Associate Editor Yulin Hswen, ScD, MPH, spoke with Robert S. Rudin, PhD, a senior information scientist at RAND, and a professor of policy analysis at the Pardee RAND Graduate School, about a randomized clinical trial published in JAMA Network Open examining the potential benefits of using AI for between-visit asthma symptom monitoring. Related Content: Between-Visit Asthma Symptom Monitoring With a Scalable Digital Intervention Discussing Digital Interventions in Asthma Symptom Monitoring
The Dana-Farber Cancer Institute (DFCI)'s MatchMiner tool was developed to increase historically low clinical trial enrollment rates in adults with cancer. Roy Perlis, MD, MSc, Editor in Chief of JAMA+ AI, spoke with Kenneth Kehl, MD, MPH, about his recent study published in JAMA Network Open evaluating the AI tool's ability to fulfill its purpose through genome sequencing. Related Content: Clinical Trial Notifications Triggered by Artificial Intelligence–Detected Cancer Progression Considerations in Translating AI to Improve Care How AI Could Increase Clinical Trial Enrollment in Adults With Cancer
Delaying diagnosis of parkinsonism can mean delaying care. In a study recently published in JAMA Neurology, David Vaillancourt, PhD, and colleagues tested the ability of an AI model to differentiate between Parkinson disease and other neurodegenerative disorders when paired with MRI. He joins JAMA and JAMA+ AI Associate Editor Yulin Hswen, ScD, MPH to discuss. Related Content: A Large Proportion of Parkinson Disease Diagnoses Are Wrong—Here's How AI Could Help Automated Imaging Differentiation for Parkinsonism
Employer-sponsored digital health solutions help patients with behavioral health conditions increase workplace productivity. Yulin Hswen, ScD, MPH, Associate Editor of JAMA+ AI, spoke with Molly Candon, PhD, and Adam Chekroud, PhD, about their recent work published in JAMA Network Open evaluating the financial return on investment for companies participating in these AI health care programs. Related Content: Employer-Sponsored Digital Health Platforms for Mental Wellness—A Good Investment Return on Investment of Enhanced Behavioral Health Services Return on Investment in Digital Mental Health Solutions
Susan Athey, PhD, of Standford University joins JAMA+ AI Editor in Chief Roy H. Perlis, MD, MSc, to discuss her research on machine learning to target behavioral nudges for college students and their potential implications for health care. Related Content: How an Economist's Application of Machine Learning to Target Nudges Applies to Precision Medicine
Diabetic retinopathy remains a leading cause of preventable blindness worldwide, and AI may facilitate screening, if such models continue to perform well when they are deployed in the real world. Coauthors Arthur Brant, MD, of Stanford University, and Sunny Virmani, MS, of Google join JAMA+ AI Editor in Chief Roy H. Perlis, MD, MSc, to discuss a new study published in JAMA Network Open. Related Content: Diabetic Retinopathy Is Massively Underscreened—an AI System Could Help Performance of a Deep Learning Diabetic Retinopathy Algorithm in India
A recent study published in JAMA Health Forum suggests that institutions may be able to deploy custom open-source large language models (LLMs) that run locally without sacrificing data privacy or flexibility. Coauthors Thomas A. Buckley, BS, and Arjun K. Manrai, PhD, from the Department of Biomedical Informatics at Harvard Medical School join JAMA+ AI Editor in Chief Roy H. Perlis, MD, MSc, to discuss. Related Content: Can Open-Source AI Models Diagnose Complex Cases as Well as GPT-4?
Correction: This podcast has been updated to add additional context on the frequency of false positives. Open neural tube defects affect approximately 1 in 1400 births. Daniel Herman, MD, PhD, of the University of Pennsylvania Perelman School of Medicine joins JAMA+ AI Editor in Chief Roy H. Perlis, MD, MSc, to discuss a quality improvement study examining the need to continue to incorporate race in tests that screen for these defects. Related Content: Study Findings Question Value of Including Race in Prenatal Screening for Birth Defects Reassessing the Inclusion of Race in Prenatal Screening for Open Neural Tube Defects
Artificial intelligence (AI) in health care is advancing, despite concerns about how its use may impact health disparities. Dimitri Christakis, MD, MPH, chief health officer at Special Olympics, joins JAMA Associate Editor Yulin Hswen, ScD, MPH, to discuss AI's potential role in improving health care delivery for people with intellectual and developmental disabilities. Related Content: How AI Could Improve Health Care for People With Intellectual and Developmental Disabilities How Artificial Intelligence Can Promote Inclusive Health
A recent study showed AI-assisted screening using a large language model tool reduced time to determine trial eligibility compared with manual methods. Author Alexander J. Blood, MD, MSc, cardiologist at Brigham and Women's Hospital, and Associate Director of the Accelerator for Clinical Transformation Research Group at Harvard Medical School joins JAMA Associate Editor Yulin Hswen, ScD, MPH, to discuss this topic and more. Related Content: Study Finds AI Can Quickly Prescreen Patients for Clinical Trials, Speeding Enrollment Manual vs AI-Assisted Prescreening for Trial Eligibility Using Large Language Models—A Randomized Clinical Trial
Comments
Download from Google Play
Download from App Store
United States