Abstract: In today's era everyone is trying to be conscious about health although due to workload and busy schedule one gives attention to the health when it shows any symptoms of some kind. But CKD is a disease which doesn't shows symptoms at all or in some cases it doesn't show any disease specific symptoms it is hard to predict, detect and prevent such a disease and this could be lead to permanently health damage, but machine learning can be hope in this problem it is best in prediction and analysis. By using data of CKD patients with 14 attributes and 400 record we are going to use various machine learning techniques like Decision Tree, SVM, etc. To build a model with maximum accuracy of predicting whether CKD or not and if yes then its Severity.
Keywords: CKD, Decision Tree, GFR, SVM, Machine Learning
| DOI: 10.17148/IJARCCE.2018.71021