Artificial intelligence, drug repurposing and peer review

Can traditional computational analysis and machine learning help compensate for inadequate peer review of drug-repurposing papers in the context of an infodemic?

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Bibliographic Details
Published in	Nature biotechnology Vol. 38; no. 10; pp. 1127 - 1131
Main Authors	Levin, Jeremy M., Oprea, Tudor I., Davidovich, Sagie, Clozel, Thomas, Overington, John P., Vanhaelen, Quentin, Cantor, Charles R., Bischof, Evelyne, Zhavoronkov, Alex
Format	Journal Article
Language	English
Published	New York Nature Publishing Group US 01.10.2020 Nature Publishing Group
Subjects	692/308 692/700 706/648/496 Agriculture Artificial Intelligence Bioinformatics Biomedical and Life Sciences Biomedical Engineering/Biotechnology Biomedicine Biotechnology Comment Computational Biology - trends Computer applications COVID-19 - drug therapy Drug Repositioning - trends Humans Learning algorithms Life Sciences Machine learning Medical colleges Medical research Medicine, Experimental Methods Off-label prescribing Pandemics Peer Review United States China
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ISSN	1087-0156 1546-1696 1546-1696
DOI	10.1038/s41587-020-0686-x

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Summary:	Can traditional computational analysis and machine learning help compensate for inadequate peer review of drug-repurposing papers in the context of an infodemic?
Bibliography:	SourceType-Scholarly Journals-1 ObjectType-Commentary-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23
ISSN:	1087-0156 1546-1696 1546-1696
DOI:	10.1038/s41587-020-0686-x