Predicting future hospital antimicrobial resistance prevalence using machine learning
Background: Predicting antimicrobial resistance (AMR), a top global health threat, nationwide at an aggregate hospital level could help target interventions. Using machine learning, we exploit historical AMR and antimicrobial usage to predict future AMR. Methods: Antimicrobial use and AMR prevalence...
| Päätekijät: | , , , , , , , , , , , |
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| Aineistotyyppi: | Journal article |
| Kieli: | English |
| Julkaistu: |
Nature Research
2024
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