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ASURVEY ON IMPROVING THE PERFORMANCE OF CANCER AND DIABETES DETECTION BY USINGNOVEL TECHNIQUE OF MACHINE LEARNING  

Abstract

ABSTRACT: The system allows the user to make a use of algorithms to predict the risk of diabetes mellitus in human body. The
various classification models such as Decision Tree, artificial Neural Networks, Logistic Regression, Association rules and
Naive Bayes are used in this system. Then the Random Forest technique is used to find the accuracy of each model in the
system. The dataset used is the Pima Indians Diabetes Data Set, which has the information of patients, some of them have
developing diabetes therefore, this project is aimed to create a mobile application for predicting a person’s class whether
present in of the diabetes and cancer risk or not.
Keywords: Decision tree, ANN, Health-Care
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