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Characterizing database granularity using SNOMED-CT hierarchy., , , , , , , , , and 9 other author(s). AMIA, AMIA, (2020)Phenotype Concept Set Construction from Concept Pair Likelihoods., , , , , , , , , and . AMIA, AMIA, (2020)What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization., , , , , , , , , and . ACL (1), page 10520-10542. Association for Computational Linguistics, (2023)The Medical Deconfounder: Assessing Treatment Effects with Electronic Health Records., , , , , and . MLHC, volume 106 of Proceedings of Machine Learning Research, page 490-512. PMLR, (2019)Evaluation of Large-scale Propensity Score Modeling and Covariate Balance on Potential Unmeasured Confounding in Observational Research., , , , , , and . AMIA, AMIA, (2020)The Medical Deconfounder: Assessing Treatment Effect with Electronic Health Records (EHRs)., , , , , and . CoRR, (2019)Potential Role of Clinical Trial Eligibility Criteria in Electronic Phenotyping., , , , and . MIE, volume 281 of Studies in Health Technology and Informatics, page 148-152. IOS Press, (2021)A High-Fidelity Combined ATC-Rxnorm Drug Hierarchy for Large-Scale Observational Research., , , , , and . MedInfo, volume 310 of Studies in Health Technology and Informatics, page 53-57. IOS Press, (2023)Phenotyping in distributed data networks: selecting the right codes for the right patients., , and . AMIA, AMIA, (2022)Investigating female-male differences in risk factors for myocardial infarction using OHDSI tools., , , and . AMIA, AMIA, (2019)