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Impressive work by Cat Coombes at #ANES2024! Using ML to predict social & behavioral risks for postop opioid dose escalation in veterans. Identified high-risk clusters, linking mental illness, chronic pain & social factors.#OpioidCrisis #AIinHealthcare @stanfordanes @EMARIANOMD
Great presentation by Maria Bolus at #ANES2024 on 'Perioperative Phenotyping Using a Registry-Based Learning Health System.' Exciting results from @Stanford’s Perioperative-CHOIR, tracking surgical outcomes in Veterans. @stanfordanes @emarianoMD #LearningHealthSystems
Honored to be part of the panel on Technology Innovation to Minimize Opioid Harm at #APSF2024 with Ken Johnson, @DomCarollo, @gxmathen, Lauren Lobaugh, and Amanda Hays!@APSForg
Fantastic to hear panelists at #APSF2024 discussing Opioid Safety and its impact on both patients and healthcare professionals.Big thanks @chaddb, Toby Weingarten, Patrick Burdon, and Krish Ramachandran for shedding light on critical strategies to reduce opioid harm!@APSForg
Thrilled to speak on "Augmented Intelligence to Address Gaps in Managing Risk of Opioid Harm" at next week's #APSFStoeltingConference2024! Join us to explore solutions for opioid safety. https://tinyurl.com/ycy59j48 #OpioidSafety #AI #AnesthesiaCare @APSForg @drchadb @EMARIANOMD
Great to work with @lagrahamepi
@sherrywren on using #NLP in #healthcare! @stanfordanes @EMARIANOMD @StanfordSPIRE @RAPMOnline #AI
Transparency for Machine Learning-Enabled Medical Devices: Guiding Principles
Transparency for Machine Learning-Enabled Medical Devices
For a MLMDs, effective transparency ensures that information that could impact patient risks and outcomes is communica...
www.fda.gov
Transparency for Machine Learning-Enabled Medical Devices: Guiding Principles
Transparency for Machine Learning-Enabled Medical Devices
For a MLMDs, effective transparency ensures that information that could impact patient risks and outcomes is communica...
www.fda.gov
Evaluating the role of multimodal AI within medicine #AI #NLP