Back to Search
Start Over
Methods for Detecting COVID-19 Patients Using Interval-Valued T-Spherical Fuzzy Relations and Information Measures.
- Source :
- International Journal of Information Technology & Decision Making; Mar2023, Vol. 22 Issue 2, p1033-1060, 28p
- Publication Year :
- 2023
-
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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02196220
- Volume :
- 22
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- International Journal of Information Technology & Decision Making
- Publication Type :
- Academic Journal
- Accession number :
- 161967037
- Full Text :
- https://doi.org/10.1142/S0219622022500122