UGC Approved Journal no 63975(19)

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

Volume 8 Issue 4
April-2021
eISSN: 2349-5162

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

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Published Paper ID:
JETIRER06038


Registration ID:
308593

Page Number

157-160

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Title

IDENTIFYING COVID-19 WITH NORMAL SICKNESS USING LOGISTIC REGRESSION

Abstract

Coronavirus causes symptoms like fever, body ache, dry cough, fatigue, chills, headache, loss of appetite, and loss of smell. In some people, COVID-19 causes severe symptoms like high fever, severe cough, and shortness of breath, which often indicates pneumonia. The Machine Learning (ML) model must be made to examine the information and it accepts that once contaminated individuals are not immune to the illness everlastingly, thus COVID infection happens once and afterward it can return again whenever with cutting edge changes in its qualities.

Key Words

Logistic Regression, Other diseases, Covid-19, prediction.

Cite This Article

"IDENTIFYING COVID-19 WITH NORMAL SICKNESS USING LOGISTIC REGRESSION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 4, page no.157-160, April-2021, Available :http://www.jetir.org/papers/JETIRER06038.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

"IDENTIFYING COVID-19 WITH NORMAL SICKNESS USING LOGISTIC REGRESSION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 4, page no. pp157-160, April-2021, Available at : http://www.jetir.org/papers/JETIRER06038.pdf

Publication Details

Published Paper ID: JETIRER06038
Registration ID: 308593
Published In: Volume 8 | Issue 4 | Year April-2021
DOI (Digital Object Identifier):
Page No: 157-160
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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