UGC Approved Journal no 63975(19)

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

Volume 6 Issue 5
May-2019
eISSN: 2349-5162

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

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Published Paper ID:
JETIRCQ06011


Registration ID:
217293

Page Number

56-61

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Title

A Review On: Heart Disease Prediction using Data Mining

Abstract

Data mining has an important aspect of predicting possibilities of any event. now a days health related problem can be predicted based on various classification, clustering algorithms which uses machine learning technologies and predict the possibilities of accordance. Health care specially heart related problem are now more often that we can get more data as a training purpose this will lead to better accurate prediction. Our main objective is to predict the possibilities of heart disease so that there will be less medical tests and we can save patients who doesn’t know about their disease.

Key Words

Heart disease, algorithms,ID3 Naïve bayes;

Cite This Article

"A Review On: Heart Disease Prediction using Data Mining ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.56-61, May - 2019, Available :http://www.jetir.org/papers/JETIRCQ06011.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

"A Review On: Heart Disease Prediction using Data Mining ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp56-61, May - 2019, Available at : http://www.jetir.org/papers/JETIRCQ06011.pdf

Publication Details

Published Paper ID: JETIRCQ06011
Registration ID: 217293
Published In: Volume 6 | Issue 5 | Year May-2019
DOI (Digital Object Identifier):
Page No: 56-61
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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