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Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources., , , , , , , , and . JAMIA, 22 (5): 993-1000 (2015)EXTraction of EMR numerical data: an efficient and generalizable tool to EXTEND clinical research., , , , , , and . BMC Medical Informatics Decis. Mak., 19 (1): 226:1-226:7 (2019)LATTE: Label-efficient Incident Phenotyping from Longitudinal Electronic Health Records., , , , , , , , , and 7 other author(s). CoRR, (2023)Binary acronym disambiguation in clinical notes from electronic health records with an application in computational phenotyping., , , , , , , , , and . Int. J. Medical Informatics, (2022)LATTE: Label-efficient incident phenotyping from longitudinal electronic health records., , , , , , , , , and 7 other author(s). Patterns, 5 (1): 100906 (January 2024)Clinical knowledge extraction via sparse embedding regression (KESER) with multi-center large scale electronic health record data., , , , , , , , , and 13 other author(s). npj Digit. Medicine, (2021)Semi-supervised calibration of noisy event risk (SCANER) with electronic health records., , , , , , , and . J. Biomed. Informatics, (August 2023)Multiview Incomplete Knowledge Graph Integration with application to cross-institutional EHR data harmonization., , , , , , , , , and 12 other author(s). J. Biomed. Informatics, (2022)PheProb: probabilistic phenotyping using diagnosis codes to improve power for genetic association studies., , , , , , and . J. Am. Medical Informatics Assoc., 25 (10): 1359-1365 (2018)Enabling phenotypic big data with PheNorm., , , , , , , , , and 2 other author(s). JAMIA, 25 (1): 54-60 (2018)