Utilizing Artificial Intelligence to Manage COVID-19 Scientific Evidence Torrent with Risklick AI: A Critical Tool for Pharmacology and Therapy Development.

Haas, Quentin; Alvarez, David Vicente; Borissov, Nikolay; Ferdowsi, Sohrab; von Meyenn, Leonhard; Trelle, Sven; Teodoro, Douglas; Amini, Poorya (2021). Utilizing Artificial Intelligence to Manage COVID-19 Scientific Evidence Torrent with Risklick AI: A Critical Tool for Pharmacology and Therapy Development. Pharmacology, 106(5-6), pp. 244-253. Karger 10.1159/000515908

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INTRODUCTION

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.

METHODS

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.

RESULTS

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.

DISCUSSION

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.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > CTU Bern

UniBE Contributor:

Haas, Quentin; Borissov, Nikolay; Trelle, Sven and Amini, Poorya

ISSN:

0031-7012

Publisher:

Karger

Funders:

[198] Innosuisse - Swiss Innovation Agency

Language:

English

Submitter:

Andrea Flükiger-Flückiger

Date Deposited:

07 May 2021 11:13

Last Modified:

21 May 2021 06:30

Publisher DOI:

10.1159/000515908

PubMed ID:

33910199

Uncontrolled Keywords:

Artificial intelligence COVID-19 Risklick Search platform

BORIS DOI:

10.48350/156206

URI:

https://boris.unibe.ch/id/eprint/156206

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