PREDICTION OF CHRONIC KIDNEY DISEASE USING MACHINE LEARNING

Prediction Of Chronic Kidney Disease Using Machine Learning

1Miss.Pallavi Patil, 2Raksha, 3Saisrijha N Kota, 4 Shreya Patil

1, 2,3,4 Department of Computer Science and Engineering,

Poojya Doddappa Appa College of Engineering, Kalaburagi, Karnataka, India

1pallavipatil@pdaengg.com

Abstract- Chronic Kidney Disease (CKD) or chronic renal disease is a significant problem that is steadily increasing. The survival time without kidneys is approximately 18 days, leading to a high demand for kidney transplants and dialysis. It is crucial to have reliable techniques for early CKD detection. Machine learning techniques have proven effective in predicting CKD. This study introduces a process for forecasting CKD status using clinical data, which includes data preprocessing, a missing value handling approach employing collaborative filtering, and attribute selection. Among the various machine learning methods examined, the adaboost classifier demonstrated the highest accuracy and minimal bias when predicting CKD status.

Keywords- Chronic Kidney Disease, Machine Learning, Ada boost Classifier, Classification Model.