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Translating Electronic Clinical Quality Measures to Executable, Portable, and Customizable Workflows in KNIME.

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Natural language processing to identify lupus nephritis phenotype in electronic health records., , , , , , , , , and 9 other author(s). BMC Medical Informatics Decis. Mak., 22-S (2): 348 (December 2022)Natural language processing to identify lupus nephritis phenotype in electronic health records., , , , , , , , , and 7 other author(s). CoRR, (2021)Assessing the Concordance of Clinical Classification Criteria for Lupus Between Electronic Health Records and a Physician Curated Registry., , , , , , , , and . MedInfo, volume 264 of Studies in Health Technology and Informatics, page 1466-1467. IOS Press, (2019)Developing a data element repository to support EHR-driven phenotype algorithm authoring and execution., , , , , , , , , and 2 other author(s). J. Biomed. Informatics, (2016)Design patterns for the development of electronic health record-driven phenotype extraction algorithms., , , , , , , , , and . J. Biomed. Informatics, (2014)Harmonization of Quality Data Model with HL7 FHIR to Support EHR-driven Phenotype Authoring and Execution: A Pilot Study., , , , , , , , , and 3 other author(s). AMIA, AMIA, (2015)Usability of a phenotype builder prototype and lessons learned for the design of phenotyping tools., , , , , , , , , and . AMIA, AMIA, (2015)Evaluation of the Portability of Natural Language Processing-based Computable Phenotypes in the eMERGE Network., , , , , , , , , and 15 other author(s). AMIA, AMIA, (2021)FHIRTime: Standardizing Temporal Patterns Identified from Clinical Narratives Using HL7 FHIR., , , , , , , , , and 4 other author(s). AMIA, AMIA, (2021)Multi-site Evaluation of Longitudinal Changes in Ejection Fraction in Heart Failure Patients Through Data-driven Phenotyping., , , , , , , , , and 7 other author(s). AMIA, AMIA, (2021)