Forestalling Growth Rate in Type Ii Diabetic Patients Using Data Mining and Artificial Neural Networks: An Intense Survey

Abstract

The race for urbanization and thirst for high living status leads to unhealthy life. As the result a rapid growth in number of diabetic patients in urban areas approaching to its deadline. In this situation it become a prime necessity for physicians and health workers to recognize accurate growth rate in number of diabetic patients. Artificial Neural Network is used as one of the artificial intelligent technique for forestalling growth rate of type II diabetic patients. Diabetes occurred due to increased level of glucose in blood. In this paper, an intense survey is done for the prediction of Type II diabetes using different Data Mining tools and Artificial Neural Network techniques, is presented. This survey is aimed to recognize and propose an effective technique for earlier prediction of the Type II diabetes. The data mining techniques like C4.5 Classifier, Support Vector Machine and K-Nearest Neighbour are compared for this work with Artificial Neural Network. As the results Artificial Neural Network found with a great accuracy of 89%.