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Prediction of Type II Diabetes Onset with Computed Tomography and Electronic Medical Records.

, , , , , , , , , and . ML-CDS/CLIP@MICCAI, volume 12445 of Lecture Notes in Computer Science, page 13-23. Springer, (2020)

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Prediction of Type II Diabetes Onset with Computed Tomography and Electronic Medical Records., , , , , , , , , and . ML-CDS/CLIP@MICCAI, volume 12445 of Lecture Notes in Computer Science, page 13-23. Springer, (2020)Detecting time-evolving phenotypic topics via tensor factorization on electronic health records: Cardiovascular disease case study., , , , , , , , , and . J. Biomed. Informatics, (2019)A retrospective approach to evaluating potential adverse outcomes associated with delay of procedures for cardiovascular and cancer-related diagnoses in the context of COVID-19., , , , , , , , , and 5 other author(s). J. Biomed. Informatics, (2021)Extraction of echocardiographic data from the electronic medical record is a rapid and efficient method for study of cardiac structure and function., , and . J. Clin. Bioinform., (2014)Phenotyping coronavirus disease 2019 during a global health pandemic: Lessons learned from the characterization of an early cohort., , , , , , , , , and 3 other author(s). J. Biomed. Informatics, (2021)Next-generation phenotyping: introducing phecodeX for enhanced discovery research in medical phenomics., , , , , , , , , and 16 other author(s). Bioinform., (October 2023)Impact of Sex and Gender Disparities on Computational Phenotyping: A Potential Barrier to an Equitable Learning Health System., , , , , , and . AMIA, AMIA, (2021)Interactive network-based clustering and investigation of multimorbidity association matrices with associationSubgraphs., , , , , , , , , and 10 other author(s). Bioinform., (January 2023)