Prediction of heart and kidney risks in diabetic prone population using fuzzy classification

Diabetes mellitus is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both. In current scenario diabetes mellitus has become the major health problem among the people of all ages globally. Early diagnosing of diabetic causing heart, kidney and eye complications is difficult and challenging. Data mining techniques are applied on clinical data attributes of diabetics to predict the risk factors. The aim of the paper is to develop a fuzzy classification model to predict heart and kidney complications using diabetic clinical data. In this research work a fuzzy classification model is designed and developed to predict the heart and kidney complications prone to diabetic populations. From the experimental result, the performance metrics for the risk complication of heart and kidney is found high for the diabetic population.