• RENI MR
• ANU MARIA JOYKUTTY

Pair of kidneys are vital organs for proper functioning of the human body. Failure in effective functioning can lead to CKD (Chronic Kidney Disease). CKD is a global health problem in which the kidneys decrease their shape and lose their ability to function, which makes the human body sick in the long run. Since there are no obvious symptoms during the early stages of CKD, patients often fail to detect the disease which leads to the final stage of CKD. Thus dialysis or kidney transplantation is the only solution to this. Early detection of CKD will help patients to take timely treatment and thereby decreases the progression of this disease. Machine learning models can achieve this goal due to their fast and accurate recognition performance. Those who are with Chronic Kidney Disease are not aware that the medical tests they take for other purposes sometimes contain useful information about CKD disease. This data is taken for developing the model. There are many machine learning models that exist, the aim of this study is to find the performance of each model and also aims to identify important features for creating the model without much complication.

Feature Selection; Machine Learning; Chronic Kidney Disease (CKD); KNN Imputation; Early Detection.

"Performance Analysis of Different Machine Learning Models for Early Detection of CKD", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 4, page no.1139-1146, April-2021, Available :http://www.jetir.org/papers/JETIR2104357.pdf

"Performance Analysis of Different Machine Learning Models for Early Detection of CKD", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 4, page no. pp1139-1146, April-2021, Available at : http://www.jetir.org/papers/JETIR2104357.pdf