Evidence map›Paper›PMID 33935585›Full record

ArticleInformation systems frontiers : a journal of research and innovation2021

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

Francesco Piccialli, Vincenzo Schiano di Cola, Fabio Giampaolo, Salvatore Cuomo

Open access · hybridAbstract read
In one paragraph

Article in Information systems frontiers : a journal of research and innovation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 3 pooled it
15.3field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

36 citing papers in PubMed, 3 syntheses or guidelines pooled it, 139 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Francesco PiccialliDepartment of Mathematics and Applications "R. Caccioppoli", University of Naples Federico II, Naples, 80126 Italy.ORCID 0000-0002-5179-2496
Vincenzo Schiano di ColaDepartment of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, 80125 Italy.
Fabio GiampaoloDepartment of Mathematics and Applications "R. Caccioppoli", University of Naples Federico II, Naples, 80126 Italy.
Salvatore CuomoDepartment of Mathematics and Applications "R. Caccioppoli", University of Naples Federico II, Naples, 80126 Italy.
University of Naples Federico II · ITFederico II University Hospital · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Artificial intelligenceCOVID-19Deep learningHealthcareMachine learningReviewSARS-CoV-2Survey

Identifiers

PMID33935585
PMCPMC8072097
OpenAlexW3157143019

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.