Detection of Kidney Disease Using Machine Learning

Abstract

Severe Damage to the kidneys occurs as a result of chronic kidney disease (CKD). It is a widespread health issue thatis causing many people to pass up their prime years of life. Unlikeother diseases, which may be treated if detected in the early stages, 40% of people with CKD are oblivious to the disease present. In order to determine if a patient has CKD or not, blood pressure, diabetes status and other CKD related data are obtained from participants in this study. In order to solve the issue and identify the disease at an early stage, the use of various machine learning techniques including Random Forest, Support Vector Machine and Naïve Baye’s techniques are suggested in this study. In this study,the CKD dataset is used to determine if a person will be affected in the near future.