Open Access

ARTICLE

Prediction System for Diagnosis and Detection of Coronavirus Disease-2019 (COVID-19): A Fuzzy-Soft Expert System

Wencong Liu¹, Ahmed Mostafa Khalil^2,*, 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

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.

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