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Review

Machine and Deep Learning towards COVID-19 Diagnosis and Treatment: Survey, Challenges, and Future Directions

1
Computer Science Department, Jamoum University College, Umm Al-Qura University, Jamoum 25375, Saudi Arabia
2
Department of Software Engineering, Sir Syed University of Engineering and Technology, Karachi 75300, Pakistan
3
Business Administration Department, King Abdulaziz University, Jeddah 21589, Saudi Arabia
4
Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia
5
IT Department, Jeddah Cable Company, Jeddah 31248, Saudi Arabia
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Int. J. Environ. Res. Public Health 2021, 18(3), 1117; https://doi.org/10.3390/ijerph18031117
Received: 12 December 2020 / Revised: 16 January 2021 / Accepted: 17 January 2021 / Published: 27 January 2021
(This article belongs to the Special Issue Deep Learning: AI Steps Up in Battle against COVID-19)
With many successful stories, machine learning (ML) and deep learning (DL) have been widely used in our everyday lives in a number of ways. They have also been instrumental in tackling the outbreak of Coronavirus (COVID-19), which has been happening around the world. The SARS-CoV-2 virus-induced COVID-19 epidemic has spread rapidly across the world, leading to international outbreaks. The COVID-19 fight to curb the spread of the disease involves most states, companies, and scientific research institutions. In this research, we look at the Artificial Intelligence (AI)-based ML and DL methods for COVID-19 diagnosis and treatment. Furthermore, in the battle against COVID-19, we summarize the AI-based ML and DL methods and the available datasets, tools, and performance. This survey offers a detailed overview of the existing state-of-the-art methodologies for ML and DL researchers and the wider health community with descriptions of how ML and DL and data can improve the status of COVID-19, and more studies in order to avoid the outbreak of COVID-19. Details of challenges and future directions are also provided. View Full-Text
Keywords: COVID-19; diagnosis; treatment; artificial intelligence; machine learning; deep learning COVID-19; diagnosis; treatment; artificial intelligence; machine learning; deep learning
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MDPI and ACS Style

Alafif, T.; Tehame, A.M.; Bajaba, S.; Barnawi, A.; Zia, S. Machine and Deep Learning towards COVID-19 Diagnosis and Treatment: Survey, Challenges, and Future Directions. Int. J. Environ. Res. Public Health 2021, 18, 1117. https://doi.org/10.3390/ijerph18031117

AMA Style

Alafif T, Tehame AM, Bajaba S, Barnawi A, Zia S. Machine and Deep Learning towards COVID-19 Diagnosis and Treatment: Survey, Challenges, and Future Directions. International Journal of Environmental Research and Public Health. 2021; 18(3):1117. https://doi.org/10.3390/ijerph18031117

Chicago/Turabian Style

Alafif, Tarik; Tehame, Abdul M.; Bajaba, Saleh; Barnawi, Ahmed; Zia, Saad. 2021. "Machine and Deep Learning towards COVID-19 Diagnosis and Treatment: Survey, Challenges, and Future Directions" Int. J. Environ. Res. Public Health 18, no. 3: 1117. https://doi.org/10.3390/ijerph18031117

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