JAMA+ AI Conversations

• Prescreening for Clinical Trial Eligibility Using Large Language Models

  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

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• Machine Learning for Earlier Diagnosis of Schizophrenia

  In a recent study published in JAMA Psychiatry, researchers reported that a machine learning model was able to stratify risk for subsequent diagnosis of schizophrenia or bipolar disorder among individuals already receiving psychiatric treatment. Coauthor Søren Dinesen Østergaard, PhD, of Aarhus University in Denmark joins JAMA+ AI Editor in Chief Roy H. Perlis, MD, MSc, to discuss. Related Content: Machine Learning Model Shows Promise in Early Detection of Serious Mental Illness Predicting Diagnostic Progression to Schizophrenia or Bipolar Disorder via Machine Learning

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• Language Equity in Health Technology

  AI can play a role in addressing language barriers in health care. In a recent Editorial in JAMA Network Open, Pilar Ortega, MD, MGM, of the University of Illinois College of Medicine, and coauthors emphasized the urgent need for integrating language equity into digital health solutions. Dr Ortega joins JAMA and JAMA+ AI Associate Editor Yulin Hswen, ScD, MPH, to discuss. Related Content: Researcher Proposes New Framework for Language Equity in Health Technology Language Equity in Health Technology for Patients With Non–English Language Preference Challenges to Video Visits for Patients With Non–English Language Preference

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• AI Guided Diagnostic-Quality Lung Ultrasound

  Lung ultrasound aids in the diagnosis of patients with dyspnea but requires technical proficiency for image acquisition. Cristiana Baloescu, MD, MPH, of Yale School of Medicine, joins JAMA Associate Editor Yulin Hswen, ScD, MPH, to discuss a new study published in JAMA Cardiology evaluating the ability of AI to guide acquisition of diagnostic-quality lung ultrasound images by trained health care professionals. Related Content: AI-Guided Lung Ultrasounds Could Help Nonexpert Clinicians Acquire “Expert-Level” Images Artificial Intelligence–Guided Lung Ultrasound by Nonexperts

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• Diagnosis and Treatment of Infectious Disease Using AI

  A recent study in JAMA Network Open evaluates the use of machine learning algorithms to assess the management of urinary tract infection (UTI). Author Sanjat Kanjilal, MD, MPH, professor in the Department of Population Medicine at Harvard Medical School and Harvard Pilgrim Healthcare Institute, joins JAMA Associate Editor Yulin Hswen, ScD, MPH, to discuss this topic and more. Related Content: Researchers Use Machine Learning to Put Older Clinical Guidelines to the Test Use of Machine Learning to Assess the Management of Uncomplicated Urinary Tract Infection

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