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Heart Disease Prediction System using Data Mining Clustering Techniques

Published on September 2016 by Meenu Singla, Kawaljeet Singh
journal_cover_thumbnail

International Conference on Advances in Emerging Technology
Foundation of Computer Science USA
ICAET2016 - Number 6
September 2016
Authors: Meenu Singla, Kawaljeet Singh
d5f147f1-675e-43f1-8bf4-c8a40e021373

Meenu Singla, Kawaljeet Singh . Heart Disease Prediction System using Data Mining Clustering Techniques. International Conference on Advances in Emerging Technology. ICAET2016, 6 (September 2016), 1-5.

@article{
author = { Meenu Singla, Kawaljeet Singh },
title = { Heart Disease Prediction System using Data Mining Clustering Techniques },
journal = { International Conference on Advances in Emerging Technology },
issue_date = { September 2016 },
volume = { ICAET2016 },
number = { 6 },
month = { September },
year = { 2016 },
issn = 0975-8887,
pages = { 1-5 },
numpages = 5,
url = { /proceedings/icaet2016/number6/25910-t081/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advances in Emerging Technology
%A Meenu Singla
%A Kawaljeet Singh
%T Heart Disease Prediction System using Data Mining Clustering Techniques
%J International Conference on Advances in Emerging Technology
%@ 0975-8887
%V ICAET2016
%N 6
%P 1-5
%D 2016
%I International Journal of Computer Applications
Abstract

Medical errors are generally costly and harmful. They caused a large number of deaths worldwide annually. A clinical decision support system offers the opportunity to reduce medical errors and also to improve patient safety. Certainly one of the most crucial aspect in applying such a systems is the diagnosis and therapy for heart diseases. This is because statistics demonstrate that a heart disease is one of the premiere factor behind deaths throughout the world. Data mining techniques are quite effective in designing clinical support systems and having the ability to discover hidden patterns and relationships in medical data. Till now, Data mining classification techniques is implemented to analyze the different kinds of heart based problems. This paper is aimed at developing a heart disease prediction system using data mining clustering techniques.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Heart Disease Prediction Data Mining Clustering Techniques Weka Tool