AI in Combating the COVID-19 Pandemic
Open accessAbstract
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.
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COVID-19 constituted a global health emergency, crisis, and disaster.
“COVID-19 have been not only a global health emergency, crisis and disaster [7, 8]”
From AI and data science for smart emergency, crisis and disaster resilience. (2023) · cites this paper as [7]
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Cites
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Research works printed but not linked: 1
- L. Cao and Q. Liu, "COVID-19 modeling: A review," 2021, arXiv:2104.12556. · arXiv
Cited by
Sorted by citations
AI and data science for smart emergency, crisis and disaster resilience.
Cao, L. (2023) · International journal of data science and analytics · doi:10.1007/s41060-023-00393-w · Cited by 102 · see citing works
“COVID-19 have been not only a global health emergency, crisis and disaster [7, 8], it has also overwhelmingly caused, intensified and created other ECD events, such as supply chain disconnection, misinformation, conspiracy [9], and geopolitical crises [10].”
BackgroundSelf-citation
- Authors
- Cao, L.
- Affiliations
- University of Technology Sydney (AU)
- Corresponding author
- Cao, Longbing
- ORCID
- Cao, Longbing
- Venue
- IEEE Intelligent Systems
- Published
- 2022-03-01
- Volume
- 37
- Issue
- 2
- Pages
- 3-13
- ISSN
- 1541-1672 (ISSN-L)
- 1941-1294
- PMC
- PMC9328726
- OpenAlex
- W4281394190
- Cited by
- 22
- References
- 16
- Citations by year
- 2025: 5 · 2024: 3 · 2023: 7 · 2022: 7
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- IEEE Intelligent Systems (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- ARC Discovery (DP190101079)
- Future Fellow (FT190100734)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › COVID-19 diagnosis using AI
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Keywords
- COVID-19 pandemic, SARS-CoV-2, artificial intelligence, international cooperation, pandemic preparedness
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