IRS-T2D

Abstract

Type 2 diabetes is a chronic and progressive disease with a large number of management strategies and treatment options. Doctors face a problem to concern many patients with different disease factors and many anti-diabetics drugs options to prescript treatment. Various researches have been considered the treatment of type 2 diabetes, but the individualization of the treatment that effectively control diabetes and avoids its complication has not been considered. In this paper, we present IRS-T2D, a recommendation system for individualizing the treatment of type 2 diabetes that utilized ontology and SWRL. The official documents management of type 2 diabetes were used as criteria and adapted to build ontologies. Thus, we built two OWL ontologies one for patient profiles and one for anti-diabetic drugs. The medication constraints were represented by Semantic Web Rule Language (SWRL). Finally, OWL/SWRL knowledge base is transformed to Jess reasoning engine format to build the IRS-T2D system.