title: Matching between the concepts of knowledge representation for a hypertension guideline and SNOMED CT.
abstract: To support knowledge representation for the development of an interoperable clinical decision support system for hypertension management, matching of 228 concepts for HT management was conducted between knowledge representation concepts and SNOMED CT. 86.8% of the concepts were covered by direct matching. 7.5% were covered by compositional matching, and 5.7% were covered by general matching. The authors concluded that SNOMED CT is useful for representing knowledge concepts but does not cover all concepts without loss of semantics.
authors.affiliation: R & D Center for Interoperable EHR, Seoul National University, Korea.
authors.forename: Hyun Young
authors.initials: HY
authors.lastname: Kim
authors.forename: In Sook
authors.initials: IS
authors.lastname: Cho
authors.forename: Jae Hyun
authors.initials: JH
authors.lastname: Lee
authors.forename: Ji Hyun
authors.initials: JH
authors.lastname: Kim
authors.forename: Dong Hyun
authors.initials: DH
authors.lastname: Sim
authors.forename: Yoon
authors.initials: Y
authors.lastname: Kim
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D006973:Hypertension / Q000145:classification*; D016247:Information Storage and Retrieval / Q000379:methods; D007723:Korea; D016347:Medical Records Systems, Computerized / Q000592:standards*; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods*; D017410:Practice Guidelines as Topic; D039061:Systematized Nomenclature of Medicine; D009626:Terminology as Topic