UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Volume 11 Issue 2
February-2024
eISSN: 2349-5162

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

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Published Paper ID:
JETIR2402583


Registration ID:
533399

Page Number

f697-f706

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Title

Heart Disease Prediction Using Machine Learning

Abstract

Heart attack prediction is a critical area of research, given its impact on morbidity and mortality worldwide. Early detection can empower individuals to modify their lifestyles and seek timely medical intervention. In this study, we focus on cardiovascular disease (CVD) prediction, specifically heart disease, as a crucial domain for predictive modeling.

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"Heart Disease Prediction Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 2, page no.f697-f706, February-2024, Available :http://www.jetir.org/papers/JETIR2402583.pdf

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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 Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 2, page no. ppf697-f706, February-2024, Available at : http://www.jetir.org/papers/JETIR2402583.pdf

Publication Details

Published Paper ID: JETIR2402583
Registration ID: 533399
Published In: Volume 11 | Issue 2 | Year February-2024
DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.38075
Page No: f697-f706
Country: Varanasi, Uttar Pradesh, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication
Published Paper URL :: https://www.jetir.org/view?paper=JETIR2402583
Published Paper PDF: https://www.jetir.org/papers/JETIR2402583

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