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...
Gorde:
| Egile Nagusiak: | , , |
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| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
Public Library of Science (PLoS)
2025-12-01
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| Saila: | PLoS Biology |
| Sarrera elektronikoa: | https://doi.org/10.1371/journal.pbio.3003539 |
| Etiketak: |
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