UGC Approved Journal no 63975(19)

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

Volume 9 Issue 6
June-2022
eISSN: 2349-5162

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

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Published Paper ID:
JETIRFN06011


Registration ID:
404027

Page Number

74-81

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Title

TO PREDICT HEART DISEASE BY ANALYSING ECG

Abstract

ECG abbreviated as electrocardiogram is a simple test that can be used to check the hearts rhythm and electrical activity. An ECG is often used alongside other tests to diagnose and monitor conditions affecting the heart. An electrocardiogram (ECG) is a simple test that can be used to monitor heart rate and electrical activity. The ECG is often used in conjunction with other tests to help diagnose and monitor cardiovascular conditions. Various ECG parameters such as heart rate, slope, ST stress, thallium, old ECG signal are used for analysis. Based on these ECG signal parameters, different heart disease and type of chest pain are diagnosed with respect to age.

Key Words

heart disease, machine learning (ml),chest pain type, logistic regression, ECG,thallium,slope.

Cite This Article

"TO PREDICT HEART DISEASE BY ANALYSING ECG", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.74-81, June-2022, Available :http://www.jetir.org/papers/JETIRFN06011.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

"TO PREDICT HEART DISEASE BY ANALYSING ECG", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. pp74-81, June-2022, Available at : http://www.jetir.org/papers/JETIRFN06011.pdf

Publication Details

Published Paper ID: JETIRFN06011
Registration ID: 404027
Published In: Volume 9 | Issue 6 | Year June-2022
DOI (Digital Object Identifier):
Page No: 74-81
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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