Personalized care recommendation approach for diabetes patients using ontology and SWRL

Abstract

Although there are many health organizations that publish documents of detection and self-care recommendation for diabetes patients, this information is too general and inconsistent with each patient’s conditions. This research proposed the personalized care recommendation approach for diabetes patients using ontology and SWRL. The objective is to develop the diabetes knowledge-based ontologies (DKOs) expressed in Web Ontology Language (OWL) for describing the patient profile, the general self-care practices for diabetes patients, complication, sign, symptom, and disorder of the diabetes patients. The DKOs are mapped and incorporated with rules created by using the Semantic Web Rule Language (SWRL) for inferring new knowledge or new relationships according to each patient condition. The semantic rules enable the semantic recommendation for personalized care of the diabetes patient corresponding to each patient’s condition.