Machine Learning Algorithms as a Boon for Chronic Kidney Disease Prediction

Abstract

Chronic kidney disease (CKD) is one type of condition where kidney function damage over several month or year. In body, kidney’s main task is to filter impurities and waste from blood which is flush out from body in form of urine. But because of some condition or diseases, in which the kidneys are damaged and cannot filter blood as well as it should. People with kidney disease may not feel ill or notice any symptoms in early stage but it is very serious problem as it may lead to complete failure of kidneys. Machine learning (ML) techniques are used for prediction. Here we have created machine learning model for CKD prediction. We have use three algorithms, logistic regression, support vector machine (SVM) and random forest with feature selection technique and finally applied bagging method on it. we have applied this model on chronic kidney dataset which have derived from UCI machine learning repository. This model predict person have chronic kidney disease or not.