Detection and Prediction of Diabetes Mellitus Using Back-Propagation Neural Network

Diabetes mellitus is one of the chronic disease asrecent estimation in 2015 shows 415 million people sufferingfrom diabetes worldwide and estimated to have deaths of 1.5 to 5 million each year. It is very important to forecast tool whichcan be used to determine whether someone has diabetes or not. There are some methods which produce accurate predictionand Artificial neural network using Back propagation neuralnetwork is one of them. This neural network having aninput layer with 8 parameters, one hidden layer with 10neurons and one output layer is implemented to produce goodresults. The GUI is developed to make tool user friendly so thatpatients can get accurate test results even from assistants in theabsence of a doctor. This project will help even doctors getrecords of the patient within seconds so that it will save timefor further treatment of patients. This paper summarizes theimplementation and development of the software tool built in MATLAB which will predict whether someone is diabetic or not. The performance of the BPNN used for predicting diabetes is 81 percent, which shows improvement in previous work. This is abetter method than finger stick which is very painful if carriedout more number of times.