This paper is in the following e-collection/theme issue:

Ontologies, Classifications, and Coding (243) Electronic Health Records (1068)

Published on in Vol 7, No 1 (2019): Jan-Mar

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/11487, first published .
SNOMED CT Concept Hierarchies for Computable Clinical Phenotypes From Electronic Health Record Data: Comparison of Intensional Versus Extensional Value Sets

SNOMED CT Concept Hierarchies for Computable Clinical Phenotypes From Electronic Health Record Data: Comparison of Intensional Versus Extensional Value Sets

SNOMED CT Concept Hierarchies for Computable Clinical Phenotypes From Electronic Health Record Data: Comparison of Intensional Versus Extensional Value Sets

Authors of this article:

Ling Chu1 Author Orcid Image ;   Vaishnavi Kannan1 Author Orcid Image ;   Mujeeb A Basit1 Author Orcid Image ;   Diane J Schaeflein1 Author Orcid Image ;   Adolfo R Ortuzar1 Author Orcid Image ;   Jimmie F Glorioso1 Author Orcid Image ;   Joel R Buchanan2 Author Orcid Image ;   Duwayne L Willett1 Author Orcid Image
Article Authors Cited by (11) Tweetations (5) Metrics

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  7. Matthewman J, Andresen K, Suffel A, Lin L, Schultze A, Tazare J, Bhaskaran K, Williamson E, Costello R, Quint J, Strongman H. Checklist and guidance on creating codelists for electronic health records research. NIHR Open Research 2024;4:20 View
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  10. Echefu G, Shah R, Sanchez Z, Rickards J, Brown S. Artificial intelligence: Applications in cardio-oncology and potential impact on racial disparities. American Heart Journal Plus: Cardiology Research and Practice 2024;48:100479 View