ABSTRACT
Objective To lay the foundation for the successive research on diabetes mellitus (DM) management system and provide support for the general doctors at grass root level to make decisions by developing DM ontology database and DM diagnosis and treatment database for semantic inference, reuse of DM knowledge, revealing and sharing potential DM knowledge. Methods The DM ontology was established on the Stanford University Protégé Platform according to the 7-step method and skeletal method by extracting the concepts of DM ontology database and DM diagnosis and treatment database, and their relationship from domestic DM-related clinical guidelines and knowledge of DM experts. The SWRL diagnosis and treatment rules were then composed and the semantic inference was realized using the JESS inference engine. Results The developed DM ontology database and DM diagnosis and treatment database included 233 concepts, 205 examples, 16 relationships between examples, 18 data value properties, 28 SWRL rules, which could thus realize the semantic inference. Conclusion The developed DM ontology can realize semantic inference and is thus beneficial for the application of ontology technology in diagnosis and treatment of chronic disease.
ABSTRACT
Objective To lay the foundation for the successive research on diabetes mellitus (DM) management system and provide support for the general doctors at grass root level to make decisions by developing DM ontology database and DM diagnosis and treatment database for semantic inference, reuse of DM knowledge, revealing and sharing potential DM knowledge. Methods The DM ontology was established on the Stanford University Protégé Platform according to the 7-step method and skeletal method by extracting the concepts of DM ontology database and DM diagnosis and treatment database, and their relationship from domestic DM-related clinical guidelines and knowledge of DM experts. The SWRL diagnosis and treatment rules were then composed and the semantic inference was realized using the JESS inference engine. Results The developed DM ontology database and DM diagnosis and treatment database included 233 concepts, 205 examples, 16 relationships between examples, 18 data value properties, 28 SWRL rules, which could thus realize the semantic inference. Conclusion The developed DM ontology can realize semantic inference and is thus beneficial for the application of ontology technology in diagnosis and treatment of chronic disease.