Chronic Kidney Disease Analysis using Data Mining

Authors

  • Sunil D  Department of Master of Computer Application, PES College of Engineering, Mandya, Karnataka, India
  • Prof. B. P. Sowmya  Department of Master of Computer Application, PES College of Engineering, Mandya, Karnataka, India

Keywords:

Data mining, Classification, Chronic Kidney, disease, Naive Bayes, Artificial Neural Network.

Abstract

Data mining has been a current trend for attaining Diagnostic results. Huge amount of unmined data is collected by the healthcare industry in order to discover hidden information for effective diagnosis and decision making. Data mining is the process of extracting hidden information from massive dataset, categorizing valid and unique patterns in data. There are many data mining techniques like clustering, classification, association Analysis, regression etc. The objective of our paper is to predict Chronic Kidney Disease (CKD) using classification techniques Like Naive Bayes and Artificial Neural Network (ANN). The Experimental results implemented in Rapidminer tool show that Naive Bayes produce more accurate results than Artificial Neural Network.

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Published

2017-08-31

Issue

Section

Research Articles

How to Cite

[1]
Sunil D, Prof. B. P. Sowmya, " Chronic Kidney Disease Analysis using Data Mining, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 4, pp.508-511, July-August-2017.