ISSN : 2319-7323

INTERNATIONAL JOURNAL OF COMPUTER SCIENCE ENGINEERING

ABSTRACT

Title	:	Prediction of Diabetic Chronic Kidney Disease Progression Using Data Mining Techniques
Authors	:	N. Afhami
Keywords	:	Predication,Datamining, Rule Mining, Diabetic chronic kidney disease.
Issue Date	:	Mar-Apr 2018
Abstract	:	Chronic Kidney Disease is a global public health problem. In CKD, kidneys will be damaged.Kidneys may get damaged from diabetes disease.Some patients involve in diabetes and chronic kidney disease simultaneously.The objective of this paper is to predictmortality and progression of the disease to thelast stagein patient involved with the diabetic chronic kidney disease. For this purpose, different methods of data mining have been used. Also, we extract rule with using rough set theory. Different features have been applied from diabetic chronic kidney patients, and we have been predicted the disease progression using J48, naïve Byes, Bayesian Network, SVM, SMO, Bagging, Random Forest, Multilayer Perceptron methods.In conclusion, we have compared these performances according to Recall, Precision and F-Measure. Experimental results shows Random Forest has better performance in compare with other methods.
Page(s)	:	35-40
ISSN	:	2319-7323
Source	:	Vol. 7, No. 2