CRDP: Chronic Renal Disease Prediction and Evaluation with Reduced Prominent Features

The kidneys are the prominent organs which help in the removal of waste and toxic material from the body. Kidney malfunctioning occurs due to various reasons, but if certain symptoms are ignored and not treated on time, then it may lead to persistent malfunctioning leading to Chronic Renal Disease (CRD). This condition expedites kidney failure and, in turn, death if not attended appropriately. This work depicts the appropriate, relevant, and correlated attributes among all the attributes and reduction of features in the dataset using chi-squared test on the patients’ dataset for better detection and prediction of CRD. The CRDP algorithm is implemented, and the results are predominantly used in logistic regression and K-nearest neighbor classification techniques to enhance and improve their prediction accuracy on CRD.