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Mashup Score: 7From Theory to Therapy: The Evolution of AI in Medicine with Dr. Daphne Koller | NEJM AI Grand Rounds - 22 day(s) ago
In this episode of the AI Grand Rounds podcast, Dr. Daphne Koller charts her professional trajectory, tracing her early fascination with computers to her influential role in AI and health care. Initially intrigued by the capacity of computers for decision-making based on theoretical principles, Koller witnessed her niche area — once considered peripheral to AI — grow to dominate the field. Her curiosity led her from abstract theory to practical machine learning applications and eventually to the complex world of biomedicine. Throughout the podcast, Koller shares her shift from pure computer science to the integration of machine learning in biological and medical research. She explains the unique challenges of applying AI to biology, distinguishing it from more deterministic fields, and how these complexities feed into her work at insitro, where she is leveraging AI throughout the drug discovery and development process, from disease understanding to therapeutic application and monitorin
Source: ai-podcast.nejm.orgCategories: General Medicine News, General HCPsTweet
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Mashup Score: 15Medicine as a Knowledge Processing Discipline with Dr. Zak Kohane | NEJM AI Grand Rounds - 11 month(s) ago
In this episode, Dr. Zak Kohane shares his journey into AI and medicine, reflecting on early influences from science fiction authors and programming experiences in his youth. He discusses his academic path, moving from programming and machine instruction to medical school, driven partly by practical advice and personal ambition. Kohane highlights his realization during medical school that medicine was not as scientifically advanced as he expected, motivating his interest in improving medical decision-making through AI. He recalls his time at MIT, contrasting the intellectual freedom there with today’s academic environment, and reflects on the impact of large language models in medicine, emphasizing their real-world applications and potential to transform medical practice. Kohane also discusses the importance of mentorship, his approach to nurturing talent, and the role of his department at Harvard in advancing the field of biomedical informatics. Finally, he shares insights on the NEJM
Source: ai-podcast.nejm.orgCategories: General Medicine News, General HCPsTweet
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Mashup Score: 3
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
Source: ai-podcast.nejm.orgCategories: Healthcare Professionals, Latest HeadlinesTweet
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Mashup Score: 3NEJM AI Grand Rounds | a podcast by NEJM Group - 1 year(s) ago
NEJM AI Grand Rounds, hosted by Arjun (Raj) Manrai, Ph.D. and Andrew Beam, Ph.D., features informal conversations with a variety of unique experts exploring the deep issues at the intersection of artificial intelligence, machine learning, and medicine. You…
Source: ai-podcast.nejm.orgCategories: Future of Medicine, Latest HeadlinesTweet
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Mashup Score: 0Dr. Lily Peng: AI for Ophthalmology and the Challenges of AI in the Real World | NEJM AI Grand Rounds - 1 year(s) ago
Dr. Lily Peng has driven major medical AI efforts along the long and arduous path from ideation to deployment. From publishing a landmark study in 2016 presenting an AI model to detect diabetic retinopathy in retinal fundus photographs to evaluating deep learning systems in India and Thailand, she has a unique and wide-ranging perspective on both model development and real-world validation. She…
Source: ai-podcast.nejm.orgCategories: Hem/Oncs, Latest HeadlinesTweet
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Mashup Score: 0Can AI Be Harmful? A Conversation with MIT’s Dr. Marzyeh Ghassemi | NEJM AI Grand Rounds - 1 year(s) ago
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…
Source: ai-podcast.nejm.orgCategories: Future of Medicine, Latest HeadlinesTweet
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Mashup Score: 16
Large language models (LLMs) like ChatGPT have proven highly capable of a broad array of natural language tasks including summarizing text, generating prose, and answering questions. This episode’s two guests, Dr. Alan Karthikesalingam and Vivek Natarajan of Google, describe their team’s recent efforts to adapt and evaluate LLMs for clinical applications. Alan and Vivek took very different paths…
Source: ai-podcast.nejm.orgCategories: Future of Medicine, Latest HeadlinesTweet
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Mashup Score: 7Dr. Pranav Rajpurkar on AI and Radiology | NEJM AI Grand Rounds - 2 year(s) ago
Dr. Pranav Rajpurkar has been at the forefront of medical AI for his entire career. As a graduate student in computer science at Stanford, he created some of the first AI models for radiology and created a suite of datasets and benchmarks that have been widely used by researchers across the world. Now, as a faculty member at Harvard, his group has continued to push the frontier of medical AI…
Source: ai-podcast.nejm.orgCategories: Healthcare Professionals, Latest HeadlinesTweet
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Mashup Score: 2Dr. Pranav Rajpurkar on AI and Radiology | NEJM AI Grand Rounds - 2 year(s) ago
Dr. Pranav Rajpurkar has been at the forefront of medical AI for his entire career. As a graduate student in computer science at Stanford, he created some of the first AI models for radiology and created a suite of datasets and benchmarks that have been widely used by researchers across the world. Now, as a faculty member at Harvard, his group has continued to push the frontier of medical AI…
Source: ai-podcast.nejm.orgCategories: Future of Medicine, Latest HeadlinesTweet
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Mashup Score: 1
Episode Guest: Euan Ashley, Stanford University professor and cardiologist Hosted by: Andrew Beam and Arjun Manrai Episode Summary: Dr. Euan Ashley is a pioneer. In 2010, he led the team that conducted the first clinical interpretation of a human genome, and he holds the record for the world’s fastest genomic diagnosis. He even has a Guinness World Record to prove it. In this wide-ranging…
Source: ai-podcast.nejm.orgCategories: Future of Medicine, Latest HeadlinesTweet
Great point @SeanKhozin & v much aligned with points @DaphneKoller made in @NEJM_AI podcast emphasizing ability to summarize extensive literature is a particularly helpful capability of genAI https://t.co/E7gnhCRj5J @emollick @zakkohane https://t.co/mzsGhl5F4p