Arjun K. Manrai, PhD, from Harvard Medical School, joins the discussion on the capabilities of open-source large language models (LLMs) versus proprietary ones for complex medical diagnoses. They delve into a recent study revealing that models like Meta's LLaMA 3.1 can match GPT-4's diagnostic abilities, challenging the notion of proprietary superiority. The conversation also highlights the benefits of privacy and accessibility in healthcare, and the vital role of AI chatbots in supporting physicians while underscoring the need for human oversight.

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

In this discussion, cardiologist Alexander J. Blood, an expert in cardiometabolic disease and data science, joins Yulin Hswen to explore groundbreaking advancements in clinical trial prescreening. They delve into how AI tools like the Rectifier enhance patient eligibility assessments, significantly reducing time and improving accuracy compared to manual methods. The conversation also highlights the essential role of human oversight in AI-assisted processes and the broader implications for medical research, emphasizing the future of AI in streamlining trial recruitment.

Søren Dinesen Østergaard, a professor at Aarhus University and expert in affective disorders, joins Roy H. Perlis to delve into the groundbreaking use of machine learning for predicting the onset of schizophrenia and bipolar disorder. They discuss how these models can identify at-risk patients in the critical prodromal phase, emphasizing the importance of timely diagnosis. The conversation also touches on the challenges of cross-site validation and the need for careful interpretation of predictive outcomes in diverse clinical settings.

A recent report from the Engineering Research Visioning Alliance emphasizes the urgent need for engineering-directed research to mitigate the growing threat of antimicrobial resistance. Anita Shukla, PhD, a professor of engineering at Brown University, discusses its findings with JAMA Medical News Associate Managing Editor Kate Schweitzer and presents several key opportunities. Related Content: Five Engineering Advancements That May Help Solve the Growing Threat of Antimicrobial Resistance

Pilar Ortega, a Multilingual Latina physician leader at the University of Illinois, sheds light on the crucial need for language equity in healthcare. She discusses how AI can help break down language barriers, enhancing communication for non-English speaking patients. Ortega emphasizes the importance of cultural competencies and the role families play in navigating healthcare systems. She advocates for integrating language education into medical training and highlights a new framework for using technology to ensure equitable access to healthcare.

Changes to CDC’s Website Threaten Patients, Public Health; Landmark Study of Black Women and Cancer Launches Related Content: As Missing and Altered CDC Webpages Threaten Patient Care, Efforts Grow to Fill Information Gaps Landmark Study Aims to Enroll 100 000 Black Women to Investigate Their Cancer Risks and Outcomes

Cristiana Baloescu, an Assistant Professor at Yale University specializing in emergency medicine and machine learning for ultrasound, joins Yulin Hswen to discuss cutting-edge research on AI-guided lung ultrasounds. They delve into how AI can enhance image acquisition for non-expert clinicians, improving accuracy in diagnosing dyspnea. The conversation also highlights real-world challenges in implementing this technology, particularly in resource-limited settings, and the potential for AI to transform emergency care.

Sanjat Kanjilal, an assistant professor at Harvard Medical School, explores how machine learning is reshaping the diagnosis and treatment of infectious diseases. He discusses a groundbreaking study on urinary tract infections, revealing the effectiveness of traditional antibiotics despite outdated guidelines. Kanjilal emphasizes the importance of understanding antimicrobial resistance and the challenges of biases in AI within healthcare. He advocates for better data infrastructure to harness AI's full potential in enhancing patient care and medical decision-making.