Implementation of a Web Application to Predict Diabetes Disease: An Approach Using Machine Learning Algorithm

Abstract

Diabetes is caused due to the excessive amount of sugar condensed into the blood. Currently, it is considered as one of the lethal diseases in the world. People all around the globe are affected by this severe disease knowingly or unknowingly. Other diseases like heart attack, paralyzed, kidney disease, blindness etc. are also caused by diabetes. Numerous computer-based detection systems were designed and outlined for anticipating and analyzing diabetes. Usual identifying process for diabetic patients needs more time and money. But with the rise of machine learning, we have that ability to develop a solution to this intense issue. Therefore we have developed an architecture which has the capability to predict where the patient has diabetes or not. Our main aim of this exploration is to build a web application based on the higher prediction accuracy of some powerful machine learning algorithm. We have used a benchmark dataset namely Pima Indian which is capable of predicting the onset of diabetes based on diagnostics manner. With an accuracy of 82.35% prediction rate Artificial Neural Network (ANN) shows a significant improvement of accuracy which drives us to develop an Interactive Web Application for Diabetes Prediction.