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The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data.

, , , , , and . PSB, page 18-29. (2019)

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Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data., , , , , and . CoRR, (2020)Implications of non-stationarity on predictive modeling using EHRs., and . J. Biomed. Informatics, (2015)Countdown Regression: Sharp and Calibrated Survival Predictions., , , , and . CoRR, (2018)Learning Effective Representations from Clinical Notes., , , and . CoRR, (2017)Learning Effective Treatment Pathways for Type-2 Diabetes from a clinical data warehouse., , and . AMIA, AMIA, (2016)The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data., , , , , and . CoRR, (2018)Do no harm: a roadmap for responsible machine learning for health care, , , , , , , , , and 3 other author(s). Nature Medicine, 25 (9): 1337--1340 (2019)Efficient sampling of protein conformational space using fast loop building and batch minimization on highly parallel computers., , and . J. Comput. Chem., 33 (31): 2483-2491 (2012)The Effectiveness of Transfer Learning in Electronic Health Records Data., , , , and . ICLR (Workshop), OpenReview.net, (2017)A method for systematic discovery of adverse drug events from clinical notes., , , and . J. Am. Medical Informatics Assoc., 22 (6): 1196-1204 (2015)