EconPapers    
Economics at your fingertips  
 

The Role of Artificial Intelligence in Fighting the COVID-19 Pandemic

Francesco Piccialli (), Vincenzo Schiano Cola, Fabio Giampaolo and Salvatore Cuomo
Additional contact information
Francesco Piccialli: University of Naples Federico II
Vincenzo Schiano Cola: University of Naples Federico II
Fabio Giampaolo: University of Naples Federico II
Salvatore Cuomo: University of Naples Federico II

Information Systems Frontiers, 2021, vol. 23, issue 6, No 7, 1467-1497

Abstract: Abstract The first few months of 2020 have profoundly changed the way we live our lives and carry out our daily activities. Although the widespread use of futuristic robotaxis and self-driving commercial vehicles has not yet become a reality, the COVID-19 pandemic has dramatically accelerated the adoption of Artificial Intelligence (AI) in different fields. We have witnessed the equivalent of two years of digital transformation compressed into just a few months. Whether it is in tracing epidemiological peaks or in transacting contactless payments, the impact of these developments has been almost immediate, and a window has opened up on what is to come. Here we analyze and discuss how AI can support us in facing the ongoing pandemic. Despite the numerous and undeniable contributions of AI, clinical trials and human skills are still required. Even if different strategies have been developed in different states worldwide, the fight against the pandemic seems to have found everywhere a valuable ally in AI, a global and open-source tool capable of providing assistance in this health emergency. A careful AI application would enable us to operate within this complex scenario involving healthcare, society and research.

Keywords: Artificial intelligence; COVID-19; SARS-CoV-2; Healthcare; Machine learning; Deep learning; Review; Survey (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://link.springer.com/10.1007/s10796-021-10131-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:infosf:v:23:y:2021:i:6:d:10.1007_s10796-021-10131-x

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10796

DOI: 10.1007/s10796-021-10131-x

Access Statistics for this article

Information Systems Frontiers is currently edited by Ram Ramesh and Raghav Rao

More articles in Information Systems Frontiers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:infosf:v:23:y:2021:i:6:d:10.1007_s10796-021-10131-x