Data Classification Model for Chronic Kidney Disease using data mining Technique and Visualization

Abstract

This research aims to develop and compare models for identifying chronic kidney disease patients. By using serveral Data mining techniques including K-nearest neighbor, decision tree, Random Forest, support vector machine and Naïve Bayes are used to test the classification of patients by using chronic kidney disease data from Apollo Hospital India By storing it in a relational database. Which has good efficiency, can support fast data transmission which responds to current information usage. And analyze to summarize with the image analysis system to be able to understand the information easily.