A Survey on AI-Enabled Pandemic Prediction and Prevention : What We Can Learn from COVID

Zhu, Yijie and Jiang, Richard and Ni, Qiang (2022) A Survey on AI-Enabled Pandemic Prediction and Prevention : What We Can Learn from COVID. In: Advanced Sciences and Technologies for Security Applications :. Advanced Sciences and Technologies for Security Applications . Springer, pp. 133-145. ISBN 978-3-031-04423-6

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Abstract

COVID-19 pandemic spread quickly in Wuhan, China in December 2019. This destructive infection spread quickly all over the planet, causing enormous misfortunes of individuals and property. All over the planet, researchers, clinicians and legislatures are continually looking for new technologies to against the COVID-19 pandemic. The use of artificial intelligence (AI) innovation gives a better approach to battle the pandemic. This paper sums up the exploration and utilization of AI in forecast and avoidance of COVID-19 pandemics, and the possibility of AI innovation used to fight against the pandemic in the situation of smart city.

Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
Publisher Copyright: © 2022, Springer Nature Switzerland AG.
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2200/2213
Subjects:
?? artificial intelligencecovid-19pandemic predictionpandemic preventionsafety, risk, reliability and qualitysafety researchpolitical science and international relationscomputer science applicationscomputer networks and communicationshealth, toxicology and m ??
ID Code:
224128
Deposited By:
Deposited On:
22 Nov 2024 16:00
Refereed?:
No
Published?:
Published
Last Modified:
22 Nov 2024 16:00