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A Machine Learning based Technique to Detect Kidney Disease

Dr. Farooque Azam , Akshay Jha, Arbaazkhan R Soudagar, Bijay B K, Yogesh S Pawar

Bangalore,India

Abstract— Chronic kidney disease is the term used to describe the state of the kidneys as a result of conditions like diabetes, glomerulonephritis, or high blood pressure. These problems could creep up on you slowly over a long time, frequently without any symptoms. Renal failure may eventually set in, requiring dialysis or a kidney transplant to extend life. Therefore, with early discovery and treatment, many repercussions can be avoided or postponed. This endeavour aims to improve diagnosis precision while speeding up diagnosis through the use of classification algorithms. The proposed study classifies the various stages of chronic renal illness using machine learning techniques. Results from tests utilising a variety of techniques, including Naive Bayes, Decision Trees, K-Nearest Neighbor, and Support Vector Machines.
Keywords—Chronic Kidney Disease, Machine Learning, Prediction, PCA, Co-relation Metrics, Random Forest.