A Review on the Use of Machine Learning Against the Covid-19 Pandemic
Received: 16 November 2021 | Revised: 2 December 2021 | Accepted: 11 December 2021 | Online: 12 February 2022
Corresponding author: S. A. A. Biabani
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.
Keywords:
Covid-19, machine learning, deep learning, evaluation, coronavirus, detection, prevention, treatmentDownloads
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