AI in Combating the COVID-19 Pandemic.

Cao, L

AI in Combating the COVID-19 Pandemic.

Cao, L

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Publisher:: IEEE COMPUTER SOC
Publication Type:: Journal Article
Citation:: IEEE Intell Syst, 2022, 37, (2), pp. 3-13
Issue Date:: 2022-03

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Field	Value	Language
dc.contributor.author	Cao, L https://orcid.org/0000-0003-1562-9429
dc.date.accessioned	2023-03-20T00:42:55Z
dc.date.available	2023-03-20T00:42:55Z
dc.date.issued	2022-03
dc.identifier.citation	IEEE Intell Syst, 2022, 37, (2), pp. 3-13
dc.identifier.issn	1541-1672
dc.identifier.issn	1941-1294
dc.identifier.uri	http://hdl.handle.net/10453/167667
dc.description.abstract	The SARS-CoV-2 virus, the COVID-19 disease, and the resulting pandemic have reshaped the entire world in an unprecedented manner. Massive efforts have been made by AI communities to combat the pandemic. What roles has AI played in tackling COVID-19? How has AI performed in the battle against COVID-19? Where are the gaps and opportunities? What lessons can we learn to enhance the ability of AI to battle future pandemics? These questions, despite being fundamental, are yet to be answered in full or systematically. They need to be addressed by AI communities as a priority despite the easing of the omicron infectiousness and threat. This article reviews these issues with reflections on global AI research and the literature on tackling COVID-19. It is envisaged that the demand and priority of developing "pandemic AI" will increase over time, with smart global epidemic early warning systems to be developed by a global collaborative AI effort.
dc.format	Electronic-eCollection
dc.language	eng
dc.publisher	IEEE COMPUTER SOC
dc.relation	http://purl.org/au-research/grants/arc/DP190101079
dc.relation	http://purl.org/au-research/grants/arc/FT190100734
dc.relation.ispartof	IEEE Intell Syst
dc.relation.isbasedon	10.1109/MIS.2022.3164313
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0801 Artificial Intelligence and Image Processing, 0806 Information Systems, 0906 Electrical and Electronic Engineering
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	AI in Combating the COVID-19 Pandemic.
dc.type	Journal Article
utslib.citation.volume	37
utslib.location.activity	United States
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	0806 Information Systems
utslib.for	0906 Electrical and Electronic Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
utslib.copyright.status	closed_access	*
dc.date.updated	2023-03-20T00:42:19Z
pubs.issue	2
pubs.publication-status	Published online
pubs.volume	37
utslib.citation.issue	2

Abstract:

The SARS-CoV-2 virus, the COVID-19 disease, and the resulting pandemic have reshaped the entire world in an unprecedented manner. Massive efforts have been made by AI communities to combat the pandemic. What roles has AI played in tackling COVID-19? How has AI performed in the battle against COVID-19? Where are the gaps and opportunities? What lessons can we learn to enhance the ability of AI to battle future pandemics? These questions, despite being fundamental, are yet to be answered in full or systematically. They need to be addressed by AI communities as a priority despite the easing of the omicron infectiousness and threat. This article reviews these issues with reflections on global AI research and the literature on tackling COVID-19. It is envisaged that the demand and priority of developing "pandemic AI" will increase over time, with smart global epidemic early warning systems to be developed by a global collaborative AI effort.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/167667