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The CLAIRE COVID-19 initiative: approach, experiences and recommendations

approach, experiences and recommendations
Authors: Bontempi G.; Chavarriaga R.; eD Canck H.; Girardi E.; Hoos H.; Kilbane-Dawe I.; Ball T.; +7 Authors

The CLAIRE COVID-19 initiative: approach, experiences and recommendations

Abstract

A volunteer effort by Artificial Intelligence (AI) researchers has shown it can deliver significant research outcomes rapidly to help tackle COVID-19. Within two months, CLAIRE's self-organising volunteers delivered the World's first comprehensive curated repository of COVID-19-related datasets useful for drug-repurposing, drafted review papers on the role CT/X-ray scan analysis and robotics could play, and progressed research in other areas. Given the pace required and nature of voluntary efforts, the teams faced a number of challenges. These offer insights in how better to prepare for future volunteer scientific efforts and large scale, data-dependent AI collaborations in general. We offer seven recommendations on how to best leverage such efforts and collaborations in the context of managing future crises.

Countries
Belgium, Italy, Netherlands
Keywords

Artificial intelligence, Short Communication, COVID-19, Emergency response, Informatique appliquée logiciel, Library and Information Sciences, Computer Science Applications, Artificial intelligence; COVID-19; Emergency response, Technologies de l'information et de la communication (TIC)

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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