AI and Clinical Practice: Using AI to Increase Access to Reliable Health Information

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Douglas Drachman, MD, shares late-breaking research from the annual conference of the American College of Cardiology and World Congress of Cardiology in an interview with JAMA Medical News Director Jennifer Abbasi. Dr Drachman—who chaired this year’s conference—is an interventional cardiologist at Massachusetts General Hospital, where he is also director of education in the cardiology division. Related Content: Clinical Highlights From the American College of Cardiology’s 2024 Scientific Session

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Could generative AI assist in extending access to vulnerable populations and begin to bridge the gap in disparities? In this Q&A, Davey Smith, MD, MAS, an infectious disease specialist and virologist at the University of California, San Diego, joins JAMA's Editor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, to explore the implications of large language models for improving patient outcomes. Related Content: Will Generative AI Tools Improve Access to Reliable Health Information?

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AI can understand brain signals linked to the sensory and motor processes involved in speech. In this Q&A, Edward Chang, MD, the chair and professor of neurosurgery at UCSF joins JAMA's Editor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, to discuss how AI has the potential to facilitate communication and how close AI development is to being able to translate human emotion. Related Content: Digital Avatars and Personalized Voices—How AI Is Helping to Restore Speech to Patients

Can AI enhance the speed and efficiency of interpreting ultrasounds and echocardiograms, thereby minimizing diagnostic errors? In this Q&A, Rima Arnaout, MD, a cardiologist and associate professor of medicine at the University of California-San Francisco, joins JAMA's Editor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, to discuss the transformative impact of AI on cardiac imaging. Related Content: How Machine Learning Might Help Improve Cardiac Imaging

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Automation bias and shortcuts in clinical AI models have posed significant challenges. In this Q&A, Jenna Wiens, PhD, an associate professor of Computer Science and Engineering at the University of Michigan in Ann Arbor, joins JAMA Editor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, to discuss how we can start leveraging human collaboration with AI to provide more effective health care. Related Content: Blind Spots, Shortcuts, and Automation Bias—Researchers Are Aiming to Improve AI Clinical Models

AI in clinical practice needs ethical frameworks to avert future biases. In this Q&A, Marzyeh Ghassemi, PhD, the Herman L. F. von Helmholtz Career Development Professor at MIT in Electrical Engineering and Computer Science (EECS), joins JAMA's Editor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, to discuss ethical machine learning and responsible clinical implementation. Related Content: AI Developers Should Understand the Risks of Deploying Their Clinical Tools, MIT Expert Says