Implementation of a Web Application to Predict Diabetes Disease using Machine Learning Algorithm
Thirumalai teja B
Department of Electronics and
Communication Engineering
Panimalar Institute Of Technology
Chennai, India
ronaldoteja273@gmail.com
Prasanth C
Department of Electronics and
Communication Engineering
Panimalar Institute Of Technology
Chennai, India
cprasanth104@gmail.com
Dr S. Sathiya Priya
Department of Electronics and
Communication Engineering
Panimalar Institute Of Technology
Chennai, India
ecehodpit@gmail.com
Peer Mohamed Afridi A
Department of Electronics and
Communication Engineering
Panimalar Institute Of Technology
Chennai, India
peermohamedafridia@gmail.com
Abstract— Diabetes is a disease caused by the formation of a disproportionately large amount of sugar in the blood coagulating. Today, it is one of the fatal diseases in the world. This complex illness affects people worldwide both consciously and subconsciously. Diabetes is also the reason for diseases like heart attack, paralyzed, kidney disease, blindness etc. Various type of computer based detection works are proposed in literatures for prediction and simulation of diabetes. Identifying process for diabetic patients usual required much more time and money. However, machine learning is the key to creating a solution to this agitated problem. So we have create another architecture where we have ability to predict whether the patient has diabetes or not. The main objective of this analysis is to create a web application for predicting diabetes of a user through the prediction of a high accuracy by some high power machine learning algorithm. A benchmark dataset namely Pima Indian has been used for prediction of the use diabetes based on a diagnosis. With an accuracy of 82.35%of the predicted speed of artificial neural networks (ANNs), a significant improvement in accuracy has been shown to developinteractive web applications for predicting diabetes.
Keywords— Diabetes, SVM, ANN, Naive Bayes, Min Max Scaling
