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An Enhanced Risk Prediction System for Cardiovascular Disease in India using Fuzzy Classification

by Maddula Krishnam Raju, S.K. Shafiulilah
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 126 - Number 7
Year of Publication: 2015
Authors: Maddula Krishnam Raju, S.K. Shafiulilah
10.5120/ijca2015906087

Maddula Krishnam Raju, S.K. Shafiulilah . An Enhanced Risk Prediction System for Cardiovascular Disease in India using Fuzzy Classification. International Journal of Computer Applications. 126, 7 ( September 2015), 11-16. DOI=10.5120/ijca2015906087

@article{ 10.5120/ijca2015906087,
author = { Maddula Krishnam Raju, S.K. Shafiulilah },
title = { An Enhanced Risk Prediction System for Cardiovascular Disease in India using Fuzzy Classification },
journal = { International Journal of Computer Applications },
issue_date = { September 2015 },
volume = { 126 },
number = { 7 },
month = { September },
year = { 2015 },
issn = { 0975-8887 },
pages = { 11-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume126/number7/22562-2015906087/ },
doi = { 10.5120/ijca2015906087 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:16:48.670864+05:30
%A Maddula Krishnam Raju
%A S.K. Shafiulilah
%T An Enhanced Risk Prediction System for Cardiovascular Disease in India using Fuzzy Classification
%J International Journal of Computer Applications
%@ 0975-8887
%V 126
%N 7
%P 11-16
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In recent times most of the people are very cautious about their health. Information and Communication Technology (ICT) is playing an extensive role in the development of medical domain application, which has been one of the most active research areas for the scientists and practitioners. Heart disease rates among the major cause of mortality in developing countries like India. Fuzzy System is a one of the promising method to provide insights for better evaluation of cardiovascular diseases. Over the years many developers built Knowledgebase Decision Support System (KDSS) on diseases, based on the medical expert’s information. This process is time consuming and KDSS depends on medical expert’s opinion which may be subjective. To overcome this problem, machine learning techniques have been developed to gain knowledge automatically from past information and raw data. This work propose a novel Fuzzy rule based Disease Decision Support System (FDDSS) for the diagnosis of heart disease, based on the score obtained, the knowledge automatically from the patient’s clinical data. The FDDSS predicts the Cardiovascular Diseases which was considered as the most important cause of mortality in India by the year 2015. The experimentation result proves that, the proposed FDDSS is better than existing manual and automation methods. A few FDDSS experimental outcomes will be helpful to the physicians to take accurate decisions.

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Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy logic Cardiovascular Disease Coronary Heart Disease Knowledgebase Decision Support System (KDSS) Fuzzy rule based Disease Decision Support System (FDDSS).

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