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

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 currentwork, we will propose a novel fuzzy softmodal (i.e., fuzzy-soft expert system) for early detection of COVID-19. Themain construction of the fuzzy-soft expert systemconsists of five portions. The exploratory study includes sixty patients (i.e., fortymales and twenty females) with symptoms similar to COVID-19 in (Nanjing Chest Hospital, Department of Respiratory, China). The proposed fuzzy-soft expert systemdepended 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.