Matching between the concepts of knowledge representation for a hypertension guideline and SNOMED CT.
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.
Kim
Hyun Young
HY
R & D Center for Interoperable EHR, Seoul National University, Korea.
Cho
In Sook
IS
Lee
Jae Hyun
JH
Kim
Ji Hyun
JH
Sim
Dong Hyun
DH
Kim
Yoon
Y
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