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A type-2 fuzzy rule-based model for diagnosis of COVID-19.
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- Author(s): ŞAHİN, İhsan; AKDOĞAN, Erhan; AKTAN, Mehmet Emin
- Source:
Turkish Journal of Electrical Engineering & Computer Sciences. 2023, Vol. 31 Issue 1, p39-52. 14p. - Source:
- Additional Information
- Subject Terms:
- Abstract: In this study, a type-2 fuzzy logic-based decision support system comprising clinical examination and blood test results that health professionals can use in addition to existing methods in the diagnosis of COVID-19 has been developed. The developed system consists of three fuzzy units. The first fuzzy unit produces COVID-19 positivity as a percentage according to the respiratory rate, loss of smell, and body temperature values, and the second fuzzy unit according to the C-reactive protein, lymphocyte, and D-dimer values obtained as a result of the blood tests. In the third fuzzy unit, the COVID-19 positivity risks according to the clinical examination and blood analysis results, which are the outputs of the first and second fuzzy units, are evaluated together and the result is obtained. As a result of the evaluation of the trials with 60 different scenarios by physicians, it has been revealed that the system can detect COVID-19 risk with 86.6% accuracy. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of Turkish Journal of Electrical Engineering & Computer Sciences is the property of Scientific and Technical Research Council of Turkey and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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