Methods for Detecting COVID-19 Patients Using Interval-Valued T-Spherical Fuzzy Relations and Information Measures

Yinyu Wang (), Kifayat Ullah (), Tahir Mahmood (), Harish Garg (), Lemnaouar Zedam (), Shouzhen Zeng and Xingsen Li
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Yinyu Wang: College of Economic and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, P. R. China
Kifayat Ullah: Department of Mathematics, Riphah International University Lahore Campus, Lahore 54000, Pakistan
Tahir Mahmood: Department of Mathematics and Statistics, International Islamic University Islamabad Islamabad, 44000, Pakistan
Harish Garg: School of Mathematics, Thapar Institute of Engineering & Technology, Deemed University, Patiala 147004, Punjab, India
Lemnaouar Zedam: Laboratory of Pure and Applied Mathematics, Department of Mathematics, Med Boudiaf University of Msila, Ichbilia, Msila 28000, Algeria
Shouzhen Zeng: School of Business, Ningbo University, Ningbo 315100, P. R. China
Xingsen Li: Research Institute of Extenics and Innovation Methods, Guangdong University of Technology, Guangzhou 510006, P. R. China

International Journal of Information Technology & Decision Making (IJITDM), 2023, vol. 22, issue 03, 1033-1060

Abstract: The concepts of relations and information measures have importance whenever we deal with medical diagnosis problems. The aim of this paper is to investigate the global pandemic COVID-19 scenario using relations and information measures in an interval-valued T-spherical fuzzy (IVTSF) environment. An IVTSF set (IVTSFS) allows describing four aspects of human opinions i.e., membership, abstinence, non-membership, and refusal grade that process information in a significant way and reduce information loss. We propose similarity measures and relations in the IVTSF environment and investigate their properties. Both information measures and relations are applied in a medical diagnosis problem keeping in view the global pandemic COVID-19. How to determine the diagnosis based on symptoms of a patient using similarity measures and relations is discussed. Finally, the advantages of dealing with such problems using the IVTSF framework are demonstrated with examples.

Keywords: T-spherical fuzzy set; interval-valued T-spherical fuzzy set; interval-valued T-spherical fuzzy relations; similarity measures; medical diagnosis; COVID-19 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0219622022500122

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