WEB BASED MEDICAL DIAGNOSIS SYSTEM USING ANN - ARM FOR THE DIABETES MELLITUS

Diabetes is a chronic disease and a major public health challenge worldwide. According to the International Diabetes Federation, there are currently 246 million diabetic people worldwide, and this number is expected to rise to 430 million by 2030. Furthermore, 3.8 million deaths are attributable to diabetes complications each year. It has been shown that 80% of type 2 diabetes complications can be prevented or delayed by early identification of people at risk. Early detection of diabetes would be of great value given the fact that at least 50% and 80% in some countries, of all people with diabetes are unaware of their condition and will remain unaware until complications appear. Several data mining and machine learning methods have been used for the diagnosis, prognosis, and management of diabetes.? In this study it is decided to fuse Artificial Neural Network (ANN) with Association Rule Mining (ARM) for better accuracy. The proposed study is to Design and Develop a Web based Artificial Neural Network with Association Rule Mining for the diagnosis of Diabetic Disease.?