Title :
A diabetes diagnostic domain ontology for CBR system from the conceptual model of SNOMED CT
Author :
El-Sappagh, Shaker ; El-Masri, Samir ; Elmogy, Mohammed ; Riad, Alaa M.
Author_Institution :
Fac. of Comput. & Inf., Minia Univ., Minia, Egypt
Abstract :
Domain ontology or background knowledge facilitates the implementation of knowledge intensive case based reasoning systems. Based on the conceptual model of SNOMED CT, this research will propose a methodology for building ontology for diabetes concepts based on most recent diabetes clinical guidelines. All concepts, descriptions and relationships related to diabetes mellitus diagnosis including laboratory tests will be collected from SNOMED CT standard terminology. The resulting subset will be converted into OWL ontology. The resulting ontology can be used in case based reasoning system for semantic retrieval and other tasks.
Keywords :
case-based reasoning; diseases; electronic health records; information retrieval; medical diagnostic computing; ontologies (artificial intelligence); patient diagnosis; CBR system; OWL ontology; SNOMED CT standard terminology; diabetes diagnostic domain ontology; diabetes mellitus diagnosis; knowledge intensive case-based reasoning systems; semantic retrieval; Biochemistry; Diabetes; Diseases; Medical diagnostic imaging; Ontologies; Prognostics and health management; Terminology; Case based reasoning; SNOMED CT; clinical decision support system; diabetes mellitus diagnosis and knowledge management; ontology;
Conference_Titel :
Engineering and Technology (ICET), 2014 International Conference on
Conference_Location :
Cairo
DOI :
10.1109/ICEngTechnol.2014.7016783
