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Applying linked data principles to represent patient's electronic health records at Mayo clinic: a case report., , and . IHI, page 455-464. ACM, (2012)Review and evaluation of electronic health records-driven phenotype algorithm authoring tools for clinical and translational research., , , , , , , , , and 3 other author(s). J. Am. Medical Informatics Assoc., 22 (6): 1251-1260 (2015)Identifying sub-phenotypes of acute kidney injury using structured and unstructured electronic health record data with memory networks., , , , , , , , , and 3 other author(s). J. Biomed. Informatics, (2020)Stratified Mortality Prediction of Patients with Acute Kidney Injury in Critical Care., , , , , , , , , and . MedInfo, volume 264 of Studies in Health Technology and Informatics, page 462-466. IOS Press, (2019)A Standards-based Semantic Metadata Repository to Support EHR-driven Phenotype Authoring and Execution., , , , , , , , , and . MedInfo, volume 216 of Studies in Health Technology and Informatics, page 1098. IOS Press, (2015)The Phenotype Execution and Modeling Architecture: A Roadmap Towards Next-generation Phenotyping Using EHRs., , , , , , , and . AMIA, AMIA, (2017)Identification of Alzheimer's Disease Subtypes from Electronic Health Records Using a Data-Driven Approach., , , , , , , , , and 4 other author(s). AMIA, AMIA, (2020)Evaluation of Existing Phenotype Authoring Tools for Clinical Research., , , , , , , , , and 2 other author(s). AMIA, AMIA, (2014)Applying semantic web technologies for phenome-wide scan using an electronic health record linked Biobank., , , and . J. Biomed. Semant., (2012)Identification of Predictive Sub-Phenotypes of Acute Kidney Injury using Structured and Unstructured Electronic Health Record Data with Memory Networks., , , , , , , , , and 3 other author(s). CoRR, (2019)