Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts

Version 1 : Received: 20 April 2020 / Approved: 21 April 2020 / Online: 21 April 2020 (09:01:45 CEST)

A peer-reviewed article of this Preprint also exists.

Journal reference: IEEE Access 2020, 8, 19800659
DOI: 10.1109/ACCESS.2020.3009328


The very first infected novel coronavirus case (COVID-19) was found in Hubei, China in Dec. 2019. The COVID-19 pandemic has spread over 215 countries and areas in the world, and has significantly affected every aspect of our daily lives. At the time of writing this article, the numbers of infected cases and deaths still increase significantly and have no sign of a well-controlled situation, e.g., as of 14 April 2020, a cumulative total of 1,853,265 (118,854) infected (dead) COVID-19 cases were reported in the world. Motivated by recent advances and applications of artificial intelligence (AI) and big data in various areas, this paper aims at emphasizing their importance in responding to the COVID-19 outbreak and preventing the severe effects of the COVID-19 pandemic. We firstly present an overview of AI and big data, then identify their applications in fighting against COVID-19, next highlight challenges and issues associated with state-of-the-art solutions, and finally come up with recommendations for the communications to effectively control the COVID-19 situation. It is expected that this paper provides researchers and communities with new insights into the ways AI and big data improve the COVID-19 situation, and drives further studies in stopping the COVID-19 outbreak.


COVID-19; coronavirus pandemic; big data; epidemic outbreak; artificial intelligence (AI); deep learning


MEDICINE & PHARMACOLOGY, General Medical Research

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