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Computable Phenotypes enabled by the i2b2 Validation Platform., , , , , , and . AMIA, AMIA, (2015)Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources., , , , , , , , and . JAMIA, 22 (5): 993-1000 (2015)Facilitating phenotype transfer using a common data model., , , , , , , , , and 9 other author(s). Journal of Biomedical Informatics, (2019)Strategies for maintaining patient privacy in i2b2., , , , and . JAMIA, 18 (Supplement): 103-108 (2011)Evaluation of matched control algorithms in EHR-based phenotyping studies: A case study of inflammatory bowel disease comorbidities., , , , , , , and . Journal of Biomedical Informatics, (2014)High-Throughput Multimodal Automated Phenotyping (MAP) Incorporating Natural Language Processing with Application to PheWAS., , , , , , , , , and 8 other author(s). AMIA, AMIA, (2018)Making work visible for electronic phenotype implementation: Lessons learned from the eMERGE network., , , , , , , , , and 9 other author(s). J. Biomed. Informatics, (2019)Implementing a pharmacovigilance framework using data from electronic medical records., , , , and . AMIA, AMIA, (2012)Surrogate-assisted feature extraction for high-throughput phenotyping., , , , , , , , , and 1 other author(s). JAMIA, 24 (e1): e143-e149 (2017)A case study evaluating the portability of an executable computable phenotype algorithm across multiple institutions and electronic health record environments., , , , , , , , , and 14 other author(s). JAMIA, 25 (11): 1540-1546 (2018)