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Prediction System for Diagnosis and Detection of Coronavirus Disease-2019 (COVID-19): A Fuzzy-Soft Expert System.
- Source :
- CMES-Computer Modeling in Engineering & Sciences; 2023, Vol. 135 Issue 3, p2715-2730, 16p
- Publication Year :
- 2023
-
Abstract
- In early December 2019, a new virus named “2019 novel coronavirus (2019-nCoV)” appeared in Wuhan, China. The disease quickly spread worldwide, resulting in the COVID-19 pandemic. In the current work, we will propose a novel fuzzy soft modal (i.e., fuzzy-soft expert system) for early detection of COVID-19. The main construction of the fuzzy-soft expert system consists of five portions. The exploratory study includes sixty patients (i.e., forty males and twenty females) with symptoms similar to COVID-19 in (Nanjing Chest Hospital, Department of Respiratory, China). The proposed fuzzy-soft expert system depended on five symptoms of COVID-19 (i.e., shortness of breath, sore throat, cough, fever, and age). We will use the algorithm proposed by Kong et al. to detect these patients who may suffer from COVID-19. In this way, the present system is beneficial to help the physician decide if there is any patient who has COVID-19 or not. Finally, we present the comparison between the present system and the fuzzy expert system. [ABSTRACT FROM AUTHOR]
- Subjects :
- CORONAVIRUSES
FUZZY expert systems
SARS-CoV-2
COVID-19
DIAGNOSIS
COVID-19 pandemic
Subjects
Details
- Language :
- English
- ISSN :
- 15261492
- Volume :
- 135
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- CMES-Computer Modeling in Engineering & Sciences
- Publication Type :
- Academic Journal
- Accession number :
- 160490939
- Full Text :
- https://doi.org/10.32604/cmes.2023.024755