Impact of Artificial Intelligence on COVID-19 Pandemic: A Survey of Image Processing, Tracking of Disease, Prediction of Outcomes, and Computational Medicine

Almotairi, KH; Hussein, AMA; Abualigah, L; Abujayyab, SKM; Mahmoud, EH; Ghanem, BO; Gandomi, AH

Impact of Artificial Intelligence on COVID-19 Pandemic: A Survey of Image Processing, Tracking of Disease, Prediction of Outcomes, and Computational Medicine

Almotairi, KH Hussein, AMA Abualigah, L Abujayyab, SKM Mahmoud, EH Ghanem, BO Gandomi, AH

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Publisher:: MDPI
Publication Type:: Journal Article
Citation:: Big Data and Cognitive Computing, 2023, 7, (1)
Issue Date:: 2023-03-01

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Field	Value	Language
dc.contributor.author	Almotairi, KH
dc.contributor.author	Hussein, AMA
dc.contributor.author	Abualigah, L
dc.contributor.author	Abujayyab, SKM
dc.contributor.author	Mahmoud, EH
dc.contributor.author	Ghanem, BO
dc.contributor.author	Gandomi, AH
dc.date.accessioned	2024-04-27T20:35:05Z
dc.date.available	2024-04-27T20:35:05Z
dc.date.issued	2023-03-01
dc.identifier.citation	Big Data and Cognitive Computing, 2023, 7, (1)
dc.identifier.issn	2504-2289
dc.identifier.issn	2504-2289
dc.identifier.uri	http://hdl.handle.net/10453/178415
dc.description.abstract	Integrating machine learning technologies into artificial intelligence (AI) is at the forefront of the scientific and technological tools employed to combat the COVID-19 pandemic. This study assesses different uses and deployments of modern technology for combating the COVID-19 pandemic at various levels, such as image processing, tracking of disease, prediction of outcomes, and computational medicine. The results prove that computerized tomography (CT) scans help to diagnose patients infected by COVID-19. This includes two-sided, multilobar ground glass opacification (GGO) by a posterior distribution or peripheral, primarily in the lower lobes, and fewer recurrences in the intermediate lobe. An extensive search of modern technology databases relating to COVID-19 was undertaken. Subsequently, a review of the extracted information from the database search looked at how technology can be employed to tackle the pandemic. We discussed the technological advancements deployed to alleviate the communicability and effect of the pandemic. Even though there are many types of research on the use of technology in combating COVID-19, the application of technology in combating COVID-19 is still not yet fully explored. In addition, we suggested some open research issues and challenges in deploying AI technology to combat the global pandemic.
dc.language	English
dc.publisher	MDPI
dc.relation.ispartof	Big Data and Cognitive Computing
dc.relation.isbasedon	10.3390/bdcc7010011
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.classification	46 Information and computing sciences
dc.title	Impact of Artificial Intelligence on COVID-19 Pandemic: A Survey of Image Processing, Tracking of Disease, Prediction of Outcomes, and Computational Medicine
dc.type	Journal Article
utslib.citation.volume	7
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	open_access	*
dc.date.updated	2024-04-27T20:35:03Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	7
utslib.citation.issue	1

Abstract:

Integrating machine learning technologies into artificial intelligence (AI) is at the forefront of the scientific and technological tools employed to combat the COVID-19 pandemic. This study assesses different uses and deployments of modern technology for combating the COVID-19 pandemic at various levels, such as image processing, tracking of disease, prediction of outcomes, and computational medicine. The results prove that computerized tomography (CT) scans help to diagnose patients infected by COVID-19. This includes two-sided, multilobar ground glass opacification (GGO) by a posterior distribution or peripheral, primarily in the lower lobes, and fewer recurrences in the intermediate lobe. An extensive search of modern technology databases relating to COVID-19 was undertaken. Subsequently, a review of the extracted information from the database search looked at how technology can be employed to tackle the pandemic. We discussed the technological advancements deployed to alleviate the communicability and effect of the pandemic. Even though there are many types of research on the use of technology in combating COVID-19, the application of technology in combating COVID-19 is still not yet fully explored. In addition, we suggested some open research issues and challenges in deploying AI technology to combat the global pandemic.

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http://hdl.handle.net/10453/178415