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AMIA Jt Summits Transl Sci Proc. 2012; 2012: 10–19.
Published online 2012 March 19.
PMCID: PMC3392057

Using Semantic Web Technologies for Cohort Identification from Electronic Health Records for Clinical Research

Abstract

The ability to conduct genome-wide association studies (GWAS) has enabled new exploration of how genetic variations contribute to health and disease etiology. One of the key requirements to perform GWAS is the identification of subject cohorts with accurate classification of disease phenotypes. In this work, we study how emerging Semantic Web technologies can be applied in conjunction with clinical data stored in electronic health records (EHRs) to accurately identify subjects with specific diseases for inclusion in cohort studies. In particular, we demonstrate the role of using Resource Description Framework (RDF) for representing EHR data and enabling federated querying and inferencing via standardized Web protocols for identifying subjects with Diabetes Mellitus. Our study highlights the potential of using Web-scale data federation approaches to execute complex queries.


Articles from AMIA Summits on Translational Science Proceedings are provided here courtesy of American Medical Informatics Association