UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 13 | Issue 3 | March 2026

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Published in:

Volume 11 Issue 5
May-2024
eISSN: 2349-5162

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

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Published Paper ID:
JETIR2405G71


Registration ID:
541963

Page Number

p513-p531

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Title

Post Covid Effect On Heart After Recovery on CNN

Abstract

The first global pandemic in a century is coronavirus was originated in Wuhan, China. Coronavirus is associated to Coronaviridae family together with subfamily coronavirinae and it is the third infection of coronaviruses (CoVs) between human. On outer surface of the virus there is a crown like spikes thereby referred to as corona virus. A greatly contagious and dangerous virus known as COVID-19 is caused due to severe acute respiratory syndrome that is disseminated across the globe. Heart disease has consistently been superior killer in all over the world. One year after COVID-19 infection the risk of heart issues is considerable. Such heart issues involves irregular heartbeats, heart failure which is the disability of heart to pump correctly, coronary disease which one buildup in arteries that restricts blood flow, heart attacks and more. Thus, classifying disease in earlier stage is crucial. Hence, post covid effect on heart after recovery with multilevel classification is done using Convolutional Neural Network is designed in this paper. Input image obtained from the dataset is delivered to binary image conversion and then allowed for feature extraction to extract various features, such as shape, temporal, and statistical features. After that, first level disease classification is carried out using CNN to detect whether the disease is in normal or abnormal condition. If it is categorized as abnormal, second level classification is carried out by CNN that classifies Myocardial Infarction (MI) and COVID-19 patients. Moreover, Pearson correlation coefficient is utilized for post-COVID correlation study. The experimental outcome displays that CNN attained maximum accuracy of 87.80%.

Key Words

Heart disease, Convolutional Neural Networks, coronavirus, Myocardial Infraction.

Cite This Article

"Post Covid Effect On Heart After Recovery on CNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.p513-p531, May-2024, Available :http://www.jetir.org/papers/JETIR2405G71.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

"Post Covid Effect On Heart After Recovery on CNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppp513-p531, May-2024, Available at : http://www.jetir.org/papers/JETIR2405G71.pdf

Publication Details

Published Paper ID: JETIR2405G71
Registration ID: 541963
Published In: Volume 11 | Issue 5 | Year May-2024
DOI (Digital Object Identifier):
Page No: p513-p531
Country: Guntur, Andhra , India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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