Machine learning and COVID-19: Applications, challenges, and future directions

Ali Mahmudi 1, Ehsan Borzou 1, Elahdad khashayari 1, Sam davoodi Borojia 1 and Hesam Nobahar 2, *

1 Faculty of medicine, University de Sienna, Italy.
2 Faculty of Medicine, University of Semmelweis, Budapest, Hungary.
 
Review Article
GSC Advanced Research and Reviews, 2024, 19(03), 277–281.
Article DOI: 10.30574/gscarr.2024.19.3.0201
Publication history: 
Received on 18 April 2024; revised on 06 June 2024; accepted on 08 June 2024
 
Abstract: 
The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has significantly impacted global health and economies. Machine learning (ML), a subset of artificial intelligence (AI), has played a crucial role in understanding, managing, and mitigating the effects of the pandemic. This article reviews the applications of machine learning in COVID-19 research, including diagnostics, treatment, epidemiology, and public health strategies. It also discusses the challenges faced and the potential future directions for integrating machine learning in pandemic response and preparedness.
 
Keywords: 
Machine Learning; COVID-19; Applications; Challenges; Future directions
 
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Copyright information: 
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0

 

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