Chronic Kidney Disease Prediction Using Naïve Bayesian Classifier and K-NN Machine-Learning Algorithms

Abstract

Long-term renal damage is a critical issue that has to be addressed using healthcare analytics. It is a kind of kidney disease where the kidney's functionality will be degraded over months or years. Hence, accurate prediction needs to be done so that patients can undergo proper treatment at the right time. The machine learning techniques help to accomplish this. The proposed research will examine the effectiveness of supervised or guided classification algorithms such as Naive Bayesian and K-Nearest Neighbor in predicting the disorders on the basis of accuracy. A web application will be implemented that helps doctors and patients identify the disease and undergo medication with a proper diet plan.