From the JAMA Network: Socially Assistive Robots, Part 2
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
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Can AI Improve Cost-Effectiveness of 3D Total-Body Photography?
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?
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Checking in Between Checkups: An AI App to Track Asthma Symptoms
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
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Harnessing AI and Genomics in Clinical Trial Enrollment
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
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AI-Based Analysis for Parkinsonism
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
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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