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

Ajay J. Kirtane, MD, SM, a professor of medicine at Columbia University Irving Medical Center, discusses late-breaking clinical research presented at the annual meeting of the American College of Cardiology in an interview with JAMA Medical News Director Jennifer Abbasi. Related Content:

• Heart Health Highlights From ACC—Marathon Runners and Mortality, Oral GLP-1 Drugs, and More

Axe Falls on Federal Health Workforce; Experts Say CDC Cuts Will Cost Lives Related Content:

• “Guaranteed Pandemonium” as HHS Secretary Slashes Federal Health Workforce
• Experts Say Abrupt and “Staggering” CDC Cuts Will Cost Lives

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

The US Is Suing Pharmacies for Aiding in the Opioid Crisis; Texas Measles Outbreak Spurs Call for Stronger Vaccine Advocacy; Study Finds Sleep-Related Infant Deaths Are on the Rise Related Content:

• US Government Sues Pharmacy Chains CVS and Walgreens for Their Alleged Role in the Opioid Epidemic
• Amid Texas Measles Outbreak, Clinicians Struggle to Offset Increasing Vaccine Hesitancy
• Amid Decreasing Infant Mortality, Sleep-Related Infant Deaths Are on the Rise

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

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