Biased sampling driven by bacterial population structure confounds machine learning prediction of antimicrobial resistance.
Antimicrobial resistance (AMR) poses a growing threat to human health. Increasingly, genome sequencing is being applied for the surveillance of bacterial pathogens, producing a wealth of data to train machine learning (ML) applications to predict AMR and identify resistance determinants. However, ba...
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| Hauptverfasser: | , , |
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| Format: | Artigo |
| Sprache: | Inglês |
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Public Library of Science (PLoS)
2025-12-01
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| Schriftenreihe: | PLoS Biology |
| Online-Zugang: | https://doi.org/10.1371/journal.pbio.3003539 |
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