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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 the 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

## 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.

## Keywords

APA Style
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. Computer Modeling in Engineering & Sciences, 135(3), 2715-2730. https://doi.org/10.32604/cmes.2023.024755
Vancouver Style
Liu W, Khalil AM, Basheer R, Lin Y. Prediction system for diagnosis and detection of coronavirus disease-2019 (COVID-19): A fuzzy-soft expert system. Comput Model Eng Sci. 2023;135(3):2715-2730 https://doi.org/10.32604/cmes.2023.024755
IEEE Style
W. Liu, A.M. Khalil, R. Basheer, and Y. Lin "Prediction System for Diagnosis and Detection of Coronavirus Disease-2019 (COVID-19): A Fuzzy-Soft Expert System," Comput. Model. Eng. Sci., vol. 135, no. 3, pp. 2715-2730. 2023. https://doi.org/10.32604/cmes.2023.024755

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