NEJM AI Grand Rounds

In this episode of NEJM AI Grand Rounds, hosts Raj Manrai and Andy Beam interview Dr. David Ouyang, a cardiologist and AI researcher at Cedars-Sinai Medical Center. The conversation explores Ouyang’s journey from medical training to AI research and entrepreneurship, his groundbreaking work in applying AI to cardiology imaging, and the challenges of bringing AI innovations from academia to clinical practice. Ouyang discusses his experience conducting randomized controlled trials (RCTs) for AI algorithms in echocardiography, the process of commercializing research through Y Combinator, and the hurdles in reimbursement for AI-based medical devices. The episode also delves into the future of AI in cardiology, the importance of clinician involvement in AI development, and the potential impact of large language models (LLMs) on medical practice. Ouyang shares insights on balancing clinical value with business considerations in health care AI and offers advice for researchers looking to conduct clinical trials for AI technologies. Transcript.

In this engaging conversation, Noa Dagan and Ran Balicer from the Clalit Research Institute share insights into their innovative work with predictive models in healthcare. They discuss leveraging a unique dataset to enhance Hepatitis C screening and how data shaped responses during the COVID-19 pandemic. The duo emphasizes the transformative power of AI in public health, plans for a digital health residency, and the importance of mentorship in emerging public health professionals. With a touch of humor, they even ponder alternative careers and favorite superpowers.

In this engaging discussion, Vijay Pande, a general partner at Andreessen Horowitz specializing in health care investments, shares his transition from academia to venture capital. He discusses the transformative potential of AI in health care, addressing both challenges and opportunities. Pande emphasizes the need for interdisciplinary work between medical professionals and AI specialists to revolutionize patient care. He also dives into competitive dynamics among AI models and reflects on how AI could democratize health access, reminiscent of past technological revolutions.

Dr. Rohaid Ali and Dr. Fatima Mirza, chief residents at Brown University, dive into their innovative applications of AI in healthcare. They discuss transforming surgical consent forms with ChatGPT for better patient understanding and creating a custom AI-generated voice for a young patient who lost hers to a brain tumor. Balancing personal and professional dynamics as a couple, they share stories from their journeys and playful insights through a newlywed game segment, while emphasizing the importance of equitable access and responsible AI deployment in medicine.

Dr. Adam Rodman, a physician interested in AI and medicine, discusses the evolution of clinical reasoning, probabilistic models, AI in diagnostics, and his work with GPT-4. He emphasizes the need for collaboration between computer scientists and medical professionals to harness AI's potential while avoiding misapplications.

Dr. Nigam Shah, a distinguished Professor of Medicine at Stanford University, discusses the transformative impact of computational tools in healthcare, the integration of AI into clinical settings, the importance of data quality in training AI systems, and the democratization of medical knowledge. The conversation also explores the role of open-source models, the application of AI in administrative tasks at Stanford healthcare, and the potential of large language models in medicine.

Dr. Daphne Koller, an AI and health care expert, discusses her evolution from theoretical AI to practical machine learning applications. She explores the challenges of applying AI to biology and highlights its potential in drug discovery. Koller advocates for democratizing AI to enable broader participation in scientific inquiry.

Dr. Eric Horvitz shares his journey from neurobiology to AI in medicine. Discusses importance of probabilistic models and decision theory in AI. Reflects on responsible AI development. Explores applications of GPT-4 in medicine and legacy of ethical AI leadership. Navigating complex terrain of AI ethics.

Expert in AI research, James Zou, discusses the future of multi-modal AI in medicine. Topics include using social media for medical data, ethical implications of AI, and challenges of model drift. Explore the convergence of genomics, machine learning, and medicine, as well as the unique use of Twitter for medical image discussions. Learn about training AI algorithms in medicine and the behavior changes of Chat GPT-4 over time. Dive into personal interests and AI art perception in the field of medicine.

Dr. Roxana Daneshjou, Assistant professor at Stanford specializing in dermatology, shares her journey in AI research. She discusses AI fairness and bias in dermatology and the challenges of integrating language models in healthcare. Dr. Daneshjou emphasizes the need for interdisciplinary collaboration and highlights the importance of addressing disparities in AI performance across diverse skin tones.