UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 6 Issue 6
June-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRDB06004


Registration ID:
221441

Page Number

17-26

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Title

Heart Disease Prediction System using Data Mining Techniques

Abstract

Cardiovascular disease is one of the most prevalent causes of death around the world and has deemed as a vital illness in older and Middle ages. Coronary artery disease is a general cardiovascular disease involving high death rates. Angiography is more frequently than not, regarded as the best system for the examination of coronary artery disease; on the other hand, it is connected with significant side effects and high costs. Much investigation has been conveyed using data mining and machine learning to attempt alternative modalities. In this research work, a novel Thrice Filtered Information Energy based Particle Swarm optimization Feature Selection method for identifying the relevant features in the classification of heart disease. Diagnosing the existence of heart disease is really tedious process, as it entails deep knowledge and opulent experience. As a whole, the forecast of heart disease lies upon the conventional method of analysing medical report such as ECG (The Electrocardiogram), MRI (Magnetic Resonance Imaging), Blood Pressure, Stress tests by a Medicinal expert. Nowadays, a large volume of medical statistics is obtainable in medical industry and turns as a excessive source of forecasting valuable and concealed facts in almost all medical complications. Thus, these facts would really aid the doctors to create exact predictions. The innovative methods of Artificial Neural Network models have also been contributing themselves in yielding the main prediction accuracy over medical statistics. This work targets to predict the presence of heart disease utilizing back propagation MLP (Multilayer perceptron) of Artificial Neural Network with the help of MATLAB tool.

Key Words

Heart Disease, Data Mining, Feature Selection, Classification, MATLAB, Artificial Neural Network, Naïve Bayes.

Cite This Article

"Heart Disease Prediction System using Data Mining Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.17-26, June 2019, Available :http://www.jetir.org/papers/JETIRDB06004.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Heart Disease Prediction System using Data Mining Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp17-26, June 2019, Available at : http://www.jetir.org/papers/JETIRDB06004.pdf

Publication Details

Published Paper ID: JETIRDB06004
Registration ID: 221441
Published In: Volume 6 | Issue 6 | Year June-2019
DOI (Digital Object Identifier):
Page No: 17-26
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162


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