Development of knowledge-based ontology framework for diabetes patients in medical applications

Diabetes is a disease that affects an estimated 422 million adults, and the total costs of diagnosed diabetes have raised more than $245 billion. The main limitations of existing, ontology-based methods for diagnosing diabetes are that they not only have semantic inconsistencies, but also they have not provided a complete, clinical approach due to consideration of a few numbers of classes in their models. In this study, a knowledge-based ontology framework (KBOF) is developed for screening and treating diabetic patients. The proposed KBOF provides a complete semantic and clinical approach by adding more detailed analysis of patients based on a standard ontology. We have implemented the developed KBOF on Web Ontology Language (OWL), which is a semantic-web language; it enables us to create a knowledge-based representation of diabetic patients by applying different parameters. From the comparative analysis, we observed that the proposed KBOF is more feasible and accurate than traditional models for managing diabetes.