Utilizing Artificial Intelligence to Manage COVID-19 Scientific Evidence Torrent with Risklick AI: A Critical Tool for Pharmacology and Therapy Development.
Artificial Intelligence
/ statistics & numerical data
COVID-19
/ diagnosis
Clinical Trials as Topic
/ statistics & numerical data
Data Interpretation, Statistical
Drug Development
/ statistics & numerical data
Evidence-Based Medicine
/ statistics & numerical data
Humans
Pharmacology
/ statistics & numerical data
Registries
Artificial intelligence
COVID-19
Risklick
Search platform
Journal
Pharmacology
ISSN: 1423-0313
Titre abrégé: Pharmacology
Pays: Switzerland
ID NLM: 0152016
Informations de publication
Date de publication:
2021
2021
Historique:
received:
12
11
2020
accepted:
11
03
2021
pubmed:
29
4
2021
medline:
26
5
2021
entrez:
28
4
2021
Statut:
ppublish
Résumé
The SARS-CoV-2 pandemic has led to one of the most critical and boundless waves of publications in the history of modern science. The necessity to find and pursue relevant information and quantify its quality is broadly acknowledged. Modern information retrieval techniques combined with artificial intelligence (AI) appear as one of the key strategies for COVID-19 living evidence management. Nevertheless, most AI projects that retrieve COVID-19 literature still require manual tasks. In this context, we pre-sent a novel, automated search platform, called Risklick AI, which aims to automatically gather COVID-19 scientific evidence and enables scientists, policy makers, and healthcare professionals to find the most relevant information tailored to their question of interest in real time. Here, we compare the capacity of Risklick AI to find COVID-19-related clinical trials and scientific publications in comparison with clinicaltrials.gov and PubMed in the field of pharmacology and clinical intervention. The results demonstrate that Risklick AI is able to find COVID-19 references more effectively, both in terms of precision and recall, compared to the baseline platforms. Hence, Risklick AI could become a useful alternative assistant to scientists fighting the COVID-19 pandemic.
Identifiants
pubmed: 33910199
pii: 000515908
doi: 10.1159/000515908
pmc: PMC8247831
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
244-253Informations de copyright
© 2021 S. Karger AG, Basel.
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