{"title":"机器学习在新冠肺炎大流行中的应用综述","authors":"S. A. A. Biabani, N. Tayyib","doi":"10.48084/etasr.4628","DOIUrl":null,"url":null,"abstract":"Coronavirus-2019 disease (Covid-19) is a contagious respiratory disease that emerged in late 2019 and has been recognized by the World Health Organization (WHO) as a global pandemic in early 2020. Since then, researchers have been exploring various strategies and techniques to fight against this outbreak. The point when the pandemic appeared was also a period in which Machine Learning (ML) and Deep Learning (DL) algorithms were competing with traditional technologies, leading to significant findings in diverse domains. Consequently, many researchers employed ML/DL to speed up Covid-19 detection, prevention, and treatment. This paper reviews the state-of-the-art ML/DL tools used, thoroughly evaluating these techniques and their impact on the battle against Covid-19. This article aims to provide valuable insight to the researchers to assess the use of ML against the Covid-19 pandemic.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"92 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"A Review on the Use of Machine Learning Against the Covid-19 Pandemic\",\"authors\":\"S. A. A. Biabani, N. Tayyib\",\"doi\":\"10.48084/etasr.4628\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Coronavirus-2019 disease (Covid-19) is a contagious respiratory disease that emerged in late 2019 and has been recognized by the World Health Organization (WHO) as a global pandemic in early 2020. Since then, researchers have been exploring various strategies and techniques to fight against this outbreak. The point when the pandemic appeared was also a period in which Machine Learning (ML) and Deep Learning (DL) algorithms were competing with traditional technologies, leading to significant findings in diverse domains. Consequently, many researchers employed ML/DL to speed up Covid-19 detection, prevention, and treatment. This paper reviews the state-of-the-art ML/DL tools used, thoroughly evaluating these techniques and their impact on the battle against Covid-19. This article aims to provide valuable insight to the researchers to assess the use of ML against the Covid-19 pandemic.\",\"PeriodicalId\":11826,\"journal\":{\"name\":\"Engineering, Technology & Applied Science Research\",\"volume\":\"92 1\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2022-02-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering, Technology & Applied Science Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.48084/etasr.4628\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"0\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering, Technology & Applied Science Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.48084/etasr.4628","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
A Review on the Use of Machine Learning Against the Covid-19 Pandemic
Coronavirus-2019 disease (Covid-19) is a contagious respiratory disease that emerged in late 2019 and has been recognized by the World Health Organization (WHO) as a global pandemic in early 2020. Since then, researchers have been exploring various strategies and techniques to fight against this outbreak. The point when the pandemic appeared was also a period in which Machine Learning (ML) and Deep Learning (DL) algorithms were competing with traditional technologies, leading to significant findings in diverse domains. Consequently, many researchers employed ML/DL to speed up Covid-19 detection, prevention, and treatment. This paper reviews the state-of-the-art ML/DL tools used, thoroughly evaluating these techniques and their impact on the battle against Covid-19. This article aims to provide valuable insight to the researchers to assess the use of ML against the Covid-19 pandemic.