A Novel Approach to Predict Chronic Kidney Disease using Machine Learning Algorithms

Abstract

A staggering 63,538 cases have been registered according to India’s health statistics on Chronic Kidney Disease (CKD). The average age of nephropathy for humans lies between 48-70 years. CKD is more prevalent among males than females. Bitterly, India ranks among top 17 countries in CKD since 2015, which is characterized by a gradual loss of excretory organ performance over time. Earlier detection of the illness followed by treatment could keep this dreaded disease at the shore. Machine Learning, is making sensible applications in the areas such as analyzing medical science outcomes, sleuthing fraud etc. For the prediction of chronic diseases various machine learning algorithms are implemented.Our main aim is to differentiate the performance of various machine learning algorithms that are primarily based on its accuracy. This research work has idolized Rcode to compare their performance. The pivotal purpose of this study is to analyze the Chronic Kidney Disease dataset and conduct CKD and Non CKD classification cases.