Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Analysis and Prediction of Chronic Kidney Disease using Data Mining Techniques

Author : Tabassum S 1 Mamatha Bai B G 2 Jharna Majumdar 3

Date of Publication :11th September 2017

Abstract: Data Mining in Healthcare has become a present trend for obtaining accurate results of medical diagnosis, Chronic Kidney Disease (CKD) has become an international fitness problem and is a place of concern. It is a situation where kidneys turn out to be damaged and cannot filter toxic wastes within the frame. By using Data Mining Techniques, researchers have the scope to predict the Chronic Kidney Disease. This helps doctors to diagnose and suggest the treatment at an early stage. It also helps the patients to know about their health condition at an earlier stage and follow necessary diet and prescriptions.

Reference :

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    2. VeenitaKunwar and Khushboo Chandel,“Chronic Kidney Disease Analysis Using Data Mining Classification Techniques”, 6th International Conference - Cloud System and Big Data Engineering (Confluence), 2016
    3. Harshit Kumar, Nishant Singh,” Review paper on Big Data in healthcare informatics”, International Research Journal of Engineering and Technology, Feb -2017
    4. Ms. AsthaAmeta,Ms. Kalpana Jain, “Data Mining Techniques for the Prediction of Kidney Diseases and Treatment: A Review”, International Journal Of Engineering And Computer Science, Feb. 2017
    5. Viktor Medvedev, “Strategies for Big Data Clustering” IEEE 26th International Conference on Tools with Artificial Intelligence, 2014
    6. Dr. S. Vijayaran, Mr.S.Dhayanand, “Kidney Disease prediction using SVM and ANN algorithms”, International Journal of Computing and Business Research, March 2015.
    7. J Chitra Devi, “Binary Decision Tree Classification based onC4.5 and KNN Algorithm for Banking Application”, International Journal of Computational Intelligence and Informatics, September 2014
    8. http://archive.ics.uci.edu/ml/datasets/Chronic_Kidney_ Di sease.

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