z-logo
open-access-imgOpen Access
A Review on the Use of Machine Learning Against the Covid-19 Pandemic
Author(s) -
Sardar Asad Ali Biabani,
Nahla Tayyib
Publication year - 2022
Publication title -
engineering technology and applied science research
Language(s) - English
Resource type - Journals
eISSN - 2241-4487
pISSN - 1792-8036
DOI - 10.48084/etasr.4628
Subject(s) - pandemic , covid-19 , battle , outbreak , artificial intelligence , computer science , disease , data science , virology , medicine , geography , infectious disease (medical specialty) , pathology , archaeology
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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom