International Journal of Advanced Research in Computer and Communication Engineering

Abstract: Chronic Kidney Disease is a worldwide wellbeing concern and kidney infection is developing step by step. It is transforming out into a significant wellbeing concern. It is caused due by inappropriate eating regimen and less water utilization, Due to this it is critical to construct a framework that assists specialists with anticipating the CKD at a beginning phase which further aides in better investigation of the sickness, The goal here is to make a productive and powerful framework that utilizes AIML strategy to foresee CKD at a beginning phase, the information that is utilized for the testing in this framework is acquired by a number of hospitals from Tamil Nadu and the values are actual test results values that were obtained.
After the testing of the framework, the outcomes show that the LR and decision tree classifier are the two best methodologies. the testing was isolated into two areas where the main segment was incorporated to train the dataset while one more segment was utilized to assess utilizing the test dataset.

KEYWORDS: CHRONIC KIDNEY DISEASE, KNN, LOGISTIC REGRESSION, RANDOM FOREST CLASSIFIER, SVM, AND DECISION TREE CLASSIFIER.

Downloads: | DOI: 10.17148/IJARCCE.2022.11329