Open Access
ARTICLE
Prediction System for Diagnosis and Detection of Coronavirus Disease-2019 (COVID-19): A Fuzzy-Soft Expert System
Wencong Liu1, Ahmed Mostafa Khalil2,*, Rehab Basheer3, Yong Lin4
1 School of Science, Xi’an Technological University, Xi’an, 710021, China
2 Department of Mathematics, Faculty of Science, Al-Azhar University, Assiut, 71524, Egypt
3 Department of Mathematics, Faculty of Science, Assiut University, Assiut, 71516, Egypt
4 Respiratory Department of Nanjing Chest Hospital Affiliated to Southeast University, Nanjing, 210000, China
* Corresponding Author: Ahmed Mostafa Khalil. Email:
(This article belongs to this Special Issue: Application of Computer Tools in the Study of Mathematical Problems)
Computer Modeling in Engineering & Sciences 2023, 135(3), 2715-2730. https://doi.org/10.32604/cmes.2023.024755
Received 07 June 2022; Accepted 08 August 2022; Issue published 23 November 2022
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.
Graphical Abstract
Keywords
Cite This Article
Liu, W., Khalil, A. M., Basheer, R., Lin, Y. (2023). Prediction System for Diagnosis and Detection of Coronavirus Disease-2019 (COVID-19): A Fuzzy-Soft Expert System.
CMES-Computer Modeling in Engineering & Sciences, 135(3), 2715–2730.