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.

Dr. Zak Kohane, an expert in Medicine and AI, shares his journey into AI and medicine, including his early influences from science fiction authors. He discusses the impact of large language models in medicine and reflects on the challenges and opportunities in medical AI today. Kohane also talks about mentorship, nurturing talent, and the advancements of AI in the medical field, including the use of language models and the challenges of keeping educational and medical systems up to date.

In this episode, Dr. Judy Wawira Gichoya, Associate Professor in the Department of Radiology and Imaging Sciences at Emory University School of Medicine, details her journey from Kenya to the United States, from interventional radiology to artificial intelligence. Transcript. 

Vanguard geneticist Dr. George Church discusses his pioneering work in genomics and synthetic biology, including DNA sequencing and CRISPR gene editing. He shares controversial ideas about resurrecting wooly mammoths and using genome sequencing in dating apps. Dr. Church emphasizes the potential for synthetic biology and genetics to transform medicine and society, and explores the impact of AI on biology, including protein and nucleic acid design. The chapter also delves into the democratization of gene editing and AI technology and the importance of ethics and protocols.

Mark Cuban, business magnate and investor, shares his journey from self-taught programmer to successful entrepreneur. He discusses the founding story of his pharmacy benefits company and the potential of AI in healthcare. Cuban also talks about lowering drug prices, AI language models, trust in healthcare, and the future of the US healthcare system.

Dr. Atul Butte, a pioneering informatician, discusses his career, from pediatric endocrinology to trailblazing work with biomedical data. Topics include his entrepreneurial journey, the importance of utilizing electronic health record data, building neural networks in AI, the connection between pediatric endocrinology and informatics, the role of a chief data scientist in understanding human disease, the power of public speaking, the impact of the Bay Dol Act on academic researchers, managing data and infrastructure, and driving AI in medicine.

In this thought-provoking episode, Dr. Ziad Obermeyer delves into the complex issues of bias, safety, and generalizability of medical AI. Dr. Obermeyer emphasizes the importance of machine learning researchers’ task formulation, an often-overlooked yet significant determinant of bias in AI algorithms. Highlighting the dual impact of machine learning, he compares two of his works that demonstrate how AI can either exacerbate or help mitigate health care disparities. Lastly, he discusses the significant challenges encountered in the development of AI models due to siloed and inaccessible data, sharing his own experiences and solutions in tackling this issue. Dr. Obermeyer is the Blue Cross of California Distinguished Professor at the Berkeley School of Public Health, Co-Founder of Nightingale Open Science, and Co-Founder of Dandelion Health. Transcript    

Dr. Marzyeh Ghassemi has been at the forefront of medical machine learning for several years. In this episode, she describes her group’s work and her perspectives on developing and applying machine learning to understand and improve health in ways that are robust, private, and fair. Dr. Ghassemi is an Assistant Professor at MIT in Electrical Engineering and Computer Science and the Institute for Medical Engineering & Science. Transcript