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Evaluating electronic health record data sources and algorithmic approaches to identify hypertensive individuals., , , , , , , , , and 6 other author(s). J. Am. Medical Informatics Assoc., 24 (1): 162-171 (2017)Characterizing variability of electronic health record-driven phenotype definitions., , , , , , , , , and 15 other author(s). J. Am. Medical Informatics Assoc., 30 (3): 427-437 (February 2023)Portability of an algorithm to identify rheumatoid arthritis in electronic health records., , , , , , , , , and 10 other author(s). J. Am. Medical Informatics Assoc., (2012)Managing re-identification risks while providing access to the All of Us research program., , , , , , , , , and 1 other author(s). J. Am. Medical Informatics Assoc., 30 (5): 907-914 (April 2023)Comparison of family health history in surveys vs electronic health record data mapped to the observational medical outcomes partnership data model in the All of Us Research Program., , , , , , , , , and 5 other author(s). J. Am. Medical Informatics Assoc., 28 (4): 695-703 (2021)Under-specification as the source of ambiguity and vagueness in narrative phenotype algorithm definitions., , , , , , , , , and 12 other author(s). BMC Medical Informatics Decis. Mak., 22 (1): 23 (2022)The Data and Research Center of the All of Us Research Program: Framework for a National Cohort Program and Research Opportunities., , , , and . AMIA, AMIA, (2017)Self-paced Training Modality to Promote the Use of All of Us Researcher Workbench in Educational and Research Settings., , , , , , , , and . AMIA, AMIA, (2022)The All of Us Research Program: Data quality, utility, and diversity., , , , , , , , , and 38 other author(s). Patterns, 3 (8): 100570 (2022)Facilitating phenotype transfer using a common data model., , , , , , , , , and 9 other author(s). J. Biomed. Informatics, (2019)