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May 7, 2024 | 
podcasts.apple.com | Atul J. Butte |Nikhil Krishnan |Jacob Effron
Jacob and Nikhil sit down with Dr. Atul Butte, a professor at UCSF, Chief Data Scientist of the UC Health System, and a co-founder of numerous healthcare startups. They discuss Dr. Butte’s takes on healthcare AI opportunities, challenges, hype, and more.
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Apr 23, 2024 | 00061-x/fulltext?dgcid=twitter_organic_viewpoint24_landig&hss_channel=tw-27013292&sz=64)
thelancet.com | Chang Gung |Wasswa William |Atul J. Butte |Shelley Yin-Hsi Chang
SummaryWith the rapid growth of interest in and use of large language models (LLMs) across various industries, we are facing some crucial and profound ethical concerns, especially in the medical field. The unique technical architecture and purported emergent abilities of LLMs differentiate them substantially from other artificial intelligence (AI) models and natural language processing techniques used, necessitating a nuanced understanding of LLM ethics.
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Apr 2, 2024 | 
nature.com | Eduardo Rodriguez Almaraz |Madhumita Sushil |Atul J. Butte |Nikita Mehandru
Recent developments in large language models (LLMs) have unlocked opportunities for healthcare, from information synthesis to clinical decision support. These LLMs are not just capable of modeling language, but can also act as intelligent “agents” that interact with stakeholders in open-ended conversations and even influence clinical decision-making.
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Feb 22, 2024 | 
nature.com | Noah Brown |Atul J. Butte |Chris Holmes |Gilbert S. Omenn |Isaac S. Kohane
Drawing from real-life scenarios and insights shared at the RAISE (Responsible AI for Social and Ethical Healthcare) conference, we highlight the critical need for AI in health care (AIH) to primarily benefit patients and address current shortcomings in health care systems such as medical errors and access disparities.
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Feb 12, 2024 | 
ascpt.onlinelibrary.wiley.com | Sarah B Doernberg |Travis Zack |Atul J. Butte |Anu Patel
WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC? Electronic health records (EHRs) are a valuable source of real-world data that can be utilized for analysis of drug-related adverse events (AEs) not otherwise reliable from clinical trials or pharmacovigilance efforts. Machine learning is a prediction tool that can aid clinical decision making. WHAT QUESTION DID THIS STUDY ADDRESS?
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Nov 15, 2023 | 
nam.edu | Jenna Ogilvie |Debra Mathews |Amy P. Abernethy |Atul J. Butte
IntroductionThis case study was developed as one of a set of three studies, focusing on somewhat mature but rapidly evolving technologies. These case studies are intended to draw out lessons for the development of a cross-sectoral governance framework for emerging technologies in health and medicine. The focus of the case studies is the governance ecosystem in the United States, though where appropriate, the international landscape is included to provide context.
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Nov 15, 2023 | 
nam.edu | Jenna Ogilvie |Debra Mathews |Amy Lou Abernethy |Atul J. Butte
IntroductionThis case study was developed as one of a set of three studies, focusing on somewhat mature but rapidly evolving technologies. These case studies are intended to draw out lessons for the development of a cross-sectoral governance framework for emerging technologies in health and medicine. The focus of the case studies is the governance ecosystem in the United States, though where appropriate, the international landscape is included to provide context.
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Nov 1, 2023 | 
jamanetwork.com | Rebecca Voelker |Yulin Hswen |Rohan Khera |Atul J. Butte
This conversation is part of a series of interviews in which JAMA Editor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, and expert guests explore issues surrounding the rapidly evolving intersection of artificial intelligence (AI) and medicine. AI and medicine intersect on a rapidly changing terrain where the possibilities are tremendous—tools that aid in the early detection of sepsis, for example, or help streamline transitions of care.
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Aug 24, 2023 | 
jamanetwork.com | Atul J. Butte
Artificial Intelligence—From Starting Pilots to Scalable Privilege Assessment of AI Chatbot Responses to Top Searched Queries About Cancer Alexander Pan, BS; David Musheyev, BA; Daniel Bockelman, BS; Stacy Loeb, MD, MSc, PhD; Abdo E. Kabarriti, MD Use of Artificial Intelligence Chatbots for Cancer Treatment Information Shan Chen, MS; Benjamin H. Kann, MD; Michael B. Foote, MD; Hugo J. W. L. Aerts, PhD; Guergana K. Savova, PhD; Raymond H. Mak, MD; Danielle S.
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Aug 5, 2023 | 
mdpi.com | Siavash Zamirpour |Alan Hubbard |Jean Feng |Atul J. Butte
2. Materials and MethodsWe conducted a retrospective cohort study from 2016 to 2022 at the University of California, San Francisco, CA, USA, an urban quaternary academic medical center. Inclusion criteria included adult operative cases during the study period with ≥1 serum creatinine (sCr) value in the 90 days preceding surgery and ≥1 serum sCr in the 48 h following surgery ().
