A new Policy Corner argues that predictive AI can multiply the clinical and economic value of therapies by improving treatment allocation through risk-based and response-based targeting. Learn more: https://nejm.ai/4uNRshk
Most decisions aren’t uncertain — they’re almost certain. In the latest episode of the NEJM AI Grand Rounds podcast, Dr. Travis Zack of OpenEvidence explains why AI is a double-check tool. Learn more: https://nejm.ai/ep42
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A new Review Article examines MEDS, an open-source data framework designed to improve reproducibility and interoperability for AI models applied to EHR data. It highlights early gains in performance and code efficiency. Learn more: https://nejm.ai/3Q9iGjW
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A new editorial traces the evolution of medical knowledge delivery from print and search-based systems to AI-synthesis powered by LLMs. It argues that efficiency gains introduce new risks to reliability and evidence. Full editorial: https://nejm.ai/4ddmTMh
Policy Corner by David Blumenthal, MD, MPP, and Vivian S. Lee, MD, PhD, MBA: A Typology of Generative Health Care Artificial Intelligence — Definitions and Policy Implications https://nej.md/3R6WwiC
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Ambient AI documentation tools carry legal risks around consent, data transmission, and state recording laws. A new Perspective outlines strategies to mitigate liability and support transparent implementation. https://nej.md/43esKuR
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“The answer is not the important part.” In the latest episode of the NEJM AI Grand Rounds podcast, Dr. Travis Zack of OpenEvidence challenges how we measure both clinicians and AI. Hear more from Dr. Zack in the full episode: https://nejm.ai/ep42
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Perspective by T.N. Anderson et al.: Ambient AI in Clinical Practice — The Legal Landscape of Recording Consent Requirements https://nej.md/43esKuR
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A new Policy Corner examines emerging privacy risks related to AI scribes, outlining data flows and key privacy considerations, and offers best practice recommendations for health systems implementing or considering their use. Learn more: https://nejm.ai/3Pkqwaa
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Review Article by R. Goel et al.: Large Language Models in Informed Consent — Opportunities, Evidence, and Challenges https://nej.md/4nDEIrs
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