Classification of Heart Disease using Artificial Neural Network and Feature Subset Selection

M. Akhil jabbar

Classification of Heart Disease using Artificial Neural Network and Feature Subset Selection

M. Akhil jabbar * §

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§ AEC,BHONGIR ,A.P, INDIA.

Classification of Heart Disease using Artificial Neural Network and Feature Subset Selection

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Abstract

Now a day’s artificial neural network (ANN) has been widely used as a tool for solving many decision modeling problems. A multilayer perception is a feed forward ANN model that is used extensively for the solution of a no. of different problems. An ANN is the simulation of the human brain. It is a supervised learning technique used for non linear classification Coronary heart disease is major epidemic in India and Andhra Pradesh is in risk of Coronary Heart Disease. Clinical diagnosis is done mostly by doctor’s expertise and patients were asked to take no. of diagnosis tests. But all the tests will not contribute towards effective diagnosis of disease. Feature subset selection is a preprocessing step used to reduce dimensionality, remove irrelevant data. In this paper we introduce a classification approach which uses ANN and feature subset selection for the classification of heart disease. PCA is used for preprocessing and to reduce no. Of attributes which indirectly reduces the no. of diagnosis tests which are needed to be taken by a patient. We applied our approach on Andhra Pradesh heart disease data base. Our experimental results show that accuracy improved over traditional classification techniques. This system is feasible and faster and more accurate for diagnosis of heart disease.

References

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

M. Akhil jabbar. 2013. "Classification of Heart Disease using Artificial Neural Network and Feature Subset Selection". Global Journal of Computer Science and Technology - D: Neural & AI GJCST-D Volume 13 (GJCST Volume 13 Issue D3).

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GJCST Volume 13 Issue D3

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

andhra pradesh Artificial Neural Network chi-square Data mining feature subset selection genetic search heart disease principal component analy

Classification

GJCST-D Classification I.2.6

Submission ReceivedApril 12, 2013
Peer Review Double Blind
Handling Editor
Accepted May 4, 2013
Published May 15, 2013

Version of record

v1.2

Issue date

May 31, 2013

Language

English

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Article Matrices

Total Score: 143

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: M. Akhil jabbar, B.L Deekshatulu, Priti Chandra (PhD/Dr. count: 0)

View Count (all-time): 464

Total Views (Real + Logic): 3999

Total Downloads (simulated): 240

Publish Date: 2013 05, Wed

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Total Views: 4K

Total Downloads: 240

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