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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| Published in | Nature biotechnology Vol. 38; no. 10; pp. 1127 - 1131 |
|---|---|
| Main Authors | , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Nature Publishing Group US
01.10.2020
Nature Publishing Group |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1087-0156 1546-1696 1546-1696 |
| DOI | 10.1038/s41587-020-0686-x |
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| Abstract | Can traditional computational analysis and machine learning help compensate for inadequate peer review of drug-repurposing papers in the context of an infodemic? |
|---|---|
| AbstractList | Can traditional computational analysis and machine learning help compensate for inadequate peer review of drug-repurposing papers in the context of an infodemic? |
| Audience | Academic |
| Author | Zhavoronkov, Alex Oprea, Tudor I. Davidovich, Sagie Cantor, Charles R. Overington, John P. Vanhaelen, Quentin Clozel, Thomas Levin, Jeremy M. Bischof, Evelyne |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32929264$$D View this record in MEDLINE/PubMed |
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| Title | Artificial intelligence, drug repurposing and peer review |
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