JAMA+ AI Conversations

Michelle Mello, JD, PhD, MPhil, is a professor at Stanford University specializing in law and health policy. She discusses the ethical duty of healthcare organizations to disclose AI usage to patients. Mello emphasizes the current mistrust patients have regarding AI's role in their care. The conversation explores the complexities of consent and the necessity for transparent communication to enhance patient trust. Additionally, she advocates for involving patients in AI governance to create a more informed and engaged healthcare community.

David Rhew, Global Chief Medical Officer at Microsoft and Stanford adjunct professor, shares his fascinating journey from clinical practice to tech leadership. He discusses the rapid evolution of AI in healthcare, emphasizing the need for AI training in medical education. Rhew humorously illustrates the risks of over-relying on AI, likening it to becoming too dependent on GPS. He also highlights how AI can revolutionize care for underserved populations and improve drug discovery, advocating for effective adoption strategies.

Maja Matarić, a pioneering computer scientist and professor at USC, shares her expertise in socially assistive robotics. She highlights how AI is transforming therapy for autism, depression, and more. The importance of robots like Blossom is discussed, emphasizing their ability to facilitate dynamic human-robot interactions. Maja also touches on the impact of physical presence against isolation, especially during the pandemic, and envisions a future where affordable robots combat loneliness at home, enhancing well-being for all.

Daniel Lindsay, an economist from QIMR in Queensland, dives into the innovative world of 3D total-body photography for melanoma detection. He discusses the recent study on the cost-effectiveness of this technology compared to traditional methods. The conversation touches on the role of AI in enhancing lesion detection while navigating the challenges of its economic evaluation. Lindsay also highlights unexpected findings related to excisions and the implications for clinical practice, emphasizing the need for reevaluating healthcare strategies.

Robert S. Rudin, a Senior Information Scientist at RAND and a Professor of Policy Analysis, discusses a revolutionary AI app for asthma symptom tracking. He highlights how the app aims to enhance patient adherence and streamline communication with healthcare providers. The conversation dives into the collaborative design process behind the app and its user-centered focus. Rudin also addresses accessibility challenges and envisions how this technology could evolve to monitor other chronic conditions, transforming digital health management.

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

Adam Chekroud, founder of Spring Health, and Molly Candon, an economist at the University of Pennsylvania, discuss the vital role of employer-sponsored digital mental health programs. They explore the financial return on investment of these initiatives, emphasizing the increased productivity and well-being they can offer. The conversation highlights the evolution of mental health support post-pandemic and the need for integrated platforms that improve user experience and treatment effectiveness. AI's transformative potential in mental health care delivery also takes center stage.

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

Arthur Brant, Chief Resident in Ophthalmology at Stanford, and Sunny Virmani, Group Product Manager at Google, dive into the potential of AI in diabetic retinopathy screening. They discuss a groundbreaking study comparing AI's effectiveness to human evaluations, highlighting both opportunities and disparities in screening access. The conversation addresses challenges such as model drift and accountability in AI use. They stress the importance of ongoing monitoring and innovative solutions to improve patient care, especially in underserved areas.