Chronic Diseases Diagnosis using Machine Learning

Abstract

As the chronicle disease is long lasting diseases, it takes the long period to diagnosis. The chronicle disease is a threatening disease all over the world, its cost more to diagnosis, as some of the chronicle diseases are unable to diagnose, the patient has to suffer throughout his lifetime. This kind disease data are available hugely in the medical field, to make easier for healthcare system the data mining approaches are applied. As in this project, five chronicle dataset are taken and the machine learning approaches are applied, the machine learning algorithms such as decision tree, random forest, and the support vector machine are applied and the predicted whether the patient is suffering from a disease. The chronicle disease such as heart disease, liver disease, diabetes, disease dataset is retrieved from the open source and applied the data mining process to all the dataset. As we get the result by comparing all algorithms performance on all dataset the random forest predicts with high accuracy.