Ontology-based Fuzzy Inference Agent for Diabetes Classification

Abstract

Diabetes is a chronic illness that requires continuing medical care and patient self-management to prevent acute complications and to reduce the risk of long-term complications. This paper presents an ontology-based fuzzy inference agent, including a fuzzy inference engine, and a fuzzy rule base, for diabetes classification. The diabetes disease dataset used in our study is retrieved from the UCI Machine Learning Database. The experimental results indicate that the proposed approach can work effectively for classifying the diabetes.