{"title":"新型冠状病毒病-2019 (COVID-19)诊断与检测预测系统:一个模糊软专家系统","authors":"Wencong Liu, Ahmed Mostafa Khalil, Rehab Basheer, Yong Lin","doi":"10.32604/cmes.2023.024755","DOIUrl":null,"url":null,"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. © 2023 Tech Science Press. All rights reserved.","PeriodicalId":398460,"journal":{"name":"Computer Modeling in Engineering & Sciences","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prediction System for Diagnosis and Detection of Coronavirus Disease-2019 (COVID-19): A Fuzzy-Soft Expert System\",\"authors\":\"Wencong Liu, Ahmed Mostafa Khalil, Rehab Basheer, Yong Lin\",\"doi\":\"10.32604/cmes.2023.024755\",\"DOIUrl\":null,\"url\":null,\"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. © 2023 Tech Science Press. All rights reserved.\",\"PeriodicalId\":398460,\"journal\":{\"name\":\"Computer Modeling in Engineering & Sciences\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Modeling in Engineering & Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.32604/cmes.2023.024755\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Modeling in Engineering & Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32604/cmes.2023.024755","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Prediction System for Diagnosis and Detection of Coronavirus Disease-2019 (COVID-19): A Fuzzy-Soft Expert System
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. © 2023 Tech Science Press. All rights reserved.