Prediction of Diabetes Disease Using Machine Learning Model

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Abstract

As per the statistics mentioned by the world health organization, four hundred twenty-two million people in the world are suffering from diabetes which has raised the death toll to 1.6 million per year. This unprecedented growth in the number of cases and the number of casualties has led to an alarming situation because the data statistics represent a significant increase in diabetic cases among the young population, 18 years of age. Diabetes leads to various health hazards such as dysfunction of the kidney, cardiovascular problems, lower limb dismembering, and retinopathy. This article builds up a model for the prediction of diabetes using machine learning. The supervised machine learning algorithms used for prediction model such as decision tree, Naïve Bayes, artificial neural network, and logistic regression. Further, the comparison of these methods has been done base