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A Natural Language Processing Model to Identify Confidential Content in Adolescent Clinical Notes.

, , , , , , , and . Appl. Clin. Inform., 14 (3): 400-407 (May 2023)

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MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records., , , , , , , , , and 20 other author(s). CoRR, (2023)Standing on FURM ground - A framework for evaluating Fair, Useful, and Reliable AI Models in healthcare systems., , , , , , , , , and 14 other author(s). CoRR, (2024)MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records., , , , , , , , , and 20 other author(s). AAAI, page 22021-22030. AAAI Press, (2024)Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks., , , , , , , , , and 1 other author(s). J. Am. Medical Informatics Assoc., 30 (12): 2004-2011 (November 2023)A Natural Language Processing Model to Identify Confidential Content in Adolescent Clinical Notes., , , , , , , and . Appl. Clin. Inform., 14 (3): 400-407 (May 2023)A Multi-Center Study on the Adaptability of a Shared Foundation Model for Electronic Health Records., , , , , , , , and . CoRR, (2023)A survey of extant organizational and computational setups for deploying predictive models in health systems., , , and . J. Am. Medical Informatics Assoc., 28 (11): 2445-2450 (2021)The Prevalence of Confidential Content in Adolescent Progress Notes Prior to the 21st Century Cures Act Information Blocking Mandate., , , , , , , , and . Appl. Clin. Inform., 14 (2): 337-344 (March 2023)Characterizing the limitations of using diagnosis codes in the context of machine learning for healthcare., , , , , , , , , and 1 other author(s). BMC Medical Informatics Decis. Mak., 24 (1): 51 (December 2024)Instability in clinical risk stratification models using deep learning., , , , , , , , , and 2 other author(s). ML4H@NeurIPS, volume 193 of Proceedings of Machine Learning Research, page 552-565. PMLR, (2022)