Prediction of chronic kidney disease using machine learning techniques

Abstract

Chronic kidney disease (CKD) is a hazardous disease effecting many people worldwide. Individuals with chronic kidney disease (CKD) are often unaware that the medical tests they undergo may provide useful information about CKD for other purposes and this information may not be used effectively to address disease diagnosis. The major problem of this disease is it is hard to recognize till it reaches advanced stage. In this paper we are predicting chronic kidney disease(CKD) using machine learning techniques. In this paper, we are using machine learning algorithms like decision tree, naïve Bayes classification, logistic regression(LR), support vector machine(SVM) and random forest In this paper we detect the chronic kidney disease (CKD) using the best suited method and got 99.3% as the most accurate result using random forest method.