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A Data Mining Model to predict and analyze the events related to Coronary Heart Disease using Decision Trees with Particle Swarm Optimization for Feature Selection

by A. Sheik Abdullah
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 55 - Number 8
Year of Publication: 2012
Authors: A. Sheik Abdullah
10.5120/8779-2736

A. Sheik Abdullah . A Data Mining Model to predict and analyze the events related to Coronary Heart Disease using Decision Trees with Particle Swarm Optimization for Feature Selection. International Journal of Computer Applications. 55, 8 ( October 2012), 49-55. DOI=10.5120/8779-2736

@article{ 10.5120/8779-2736,
author = { A. Sheik Abdullah },
title = { A Data Mining Model to predict and analyze the events related to Coronary Heart Disease using Decision Trees with Particle Swarm Optimization for Feature Selection },
journal = { International Journal of Computer Applications },
issue_date = { October 2012 },
volume = { 55 },
number = { 8 },
month = { October },
year = { 2012 },
issn = { 0975-8887 },
pages = { 49-55 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume55/number8/8779-2736/ },
doi = { 10.5120/8779-2736 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:56:46.501715+05:30
%A A. Sheik Abdullah
%T A Data Mining Model to predict and analyze the events related to Coronary Heart Disease using Decision Trees with Particle Swarm Optimization for Feature Selection
%J International Journal of Computer Applications
%@ 0975-8887
%V 55
%N 8
%P 49-55
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Coronary Heart Disease (CHD) is a most common type of coronary disease which has no clear origin and a significant basis for premature death. Data mining has become an essential methodology for applications in medical informatics and discovering various types of diseases and syndromes. Mining valuable information and providing systematic decision-making for the diagnosis and treatment of disease from the entire database progressively becomes necessary. Classification in data mining performs an important role in data analysis and prediction. The objective of this work is to build a data mining model to be used by physicians and also to associate the risk factors related to heart disease. Data mining model has been developed using PSO – C4. 5 algorithm. The proposed model yields reduced set of features using the feature selection algorithm along with improved prediction accuracy. Thereby the developed model can be successfully used in predicting other metabolic syndromes.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Coronary Heart Disease Decision Trees Particle Swarm Optimization

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