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Factor Analysis Approach To Classify Covid-19 Datasets in Several Regions

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Date

2021

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier B.V.

Open Access Color

GOLD

Green Open Access

Yes

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Publicly Funded

No
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Top 10%
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Top 10%
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Top 10%

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Abstract

The aim of this research is to investigate the relationships between the counts of cases with Covid-19 and the deaths due to it in seven countries that are severely affected from this pandemic disease. First, the Pearson's correlation is used to determine the relationships among these countries. Then, the factor analysis is applied to categorize these countries based on their relationships. © 2021 The Authors

Description

Keywords

Coronaviruses, Correlation, Covid-19, Factor Analysis, Radiology, Nuclear Medicine and Imaging, Artificial intelligence, Statistical Analysis in Various Fields, Bioinformatics, Coronaviruses, QC1-999, Social Sciences, Geometry, Infectious disease (medical specialty), Article, mathematical analysis, Decision Sciences, FOS: Economics and business, Virology, Health Sciences, FOS: Mathematics, Pathology, Disease, Econometrics, Factor (programming language), Pandemic, Geography, Physics, Modeling the Dynamics of COVID-19 Pandemic, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Statistics, Life Sciences, Outbreak, Applications of Deep Learning in Medical Imaging, Computer science, Correlation, Programming language, Coronavirus disease 2019 (COVID-19), Categorization, Modeling and Simulation, Physical Sciences, Medicine, Factor analysis, Statistics, Probability and Uncertainty, Covid-19, 2019-20 coronavirus outbreak, Mathematics

Fields of Science

01 natural sciences, 03 medical and health sciences, 0302 clinical medicine, 0101 mathematics

Citation

Mahmoudi, Mohammad Reza...et al. (2021). "Factor analysis approach to classify COVID-19 datasets in several regions", Results in Physics, Vol. 25.

WoS Q

Q1

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Q1
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OpenCitations Citation Count
23

Source

Results in Physics

Volume

25

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Citations

CrossRef : 22

Scopus : 25

PubMed : 10

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Mendeley Readers : 29

SCOPUS™ Citations

25

checked on Apr 11, 2026

Page Views

4

checked on Apr 11, 2026

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2.3558

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