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Predictive Analysis for the Diagnosis of Coronary Artery Disease using Association Rule Mining

by Chetna Yadav, Shrikant Lade, Manish K Suman
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 87 - Number 4
Year of Publication: 2014
Authors: Chetna Yadav, Shrikant Lade, Manish K Suman
10.5120/15195-3575

Chetna Yadav, Shrikant Lade, Manish K Suman . Predictive Analysis for the Diagnosis of Coronary Artery Disease using Association Rule Mining. International Journal of Computer Applications. 87, 4 ( February 2014), 9-13. DOI=10.5120/15195-3575

@article{ 10.5120/15195-3575,
author = { Chetna Yadav, Shrikant Lade, Manish K Suman },
title = { Predictive Analysis for the Diagnosis of Coronary Artery Disease using Association Rule Mining },
journal = { International Journal of Computer Applications },
issue_date = { February 2014 },
volume = { 87 },
number = { 4 },
month = { February },
year = { 2014 },
issn = { 0975-8887 },
pages = { 9-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume87/number4/15195-3575/ },
doi = { 10.5120/15195-3575 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:05:02.755086+05:30
%A Chetna Yadav
%A Shrikant Lade
%A Manish K Suman
%T Predictive Analysis for the Diagnosis of Coronary Artery Disease using Association Rule Mining
%J International Journal of Computer Applications
%@ 0975-8887
%V 87
%N 4
%P 9-13
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, we present an improved association rule mining of data mining for the detection of Coronary Artery Disease (CAD). The whole concept behind the research is carried out by using a heart disease database, which is collected from different locations and from different patients. It is actually collected from 303 random visitors to Tehran's Shaheed Rajaei Cardiovascular, Medical and Research Centre. The mechanism proposed in this article uses the same heart disease database as input and apply the improved association rule mining method to identify the decision rules with the correctness and robustness. This paper shows conclusions of our proposed work and results.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Predictive Analysis

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