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Prediction of risk of acquiring urinary tract infection during hospital stay based on machine-learning: A retrospective cohort study
BACKGROUND: Healthcare associated infections (HAI) are a major burden for the healthcare system and associated with prolonged hospital stay, increased morbidity, mortality and costs. Healthcare associated urinary tract infections (HA-UTI) accounts for about 20–30% of all HAI’s, and with the emergenc...
Zapisane w:
| Wydane w: | PLoS One |
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| Główni autorzy: | , , |
| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
Public Library of Science
2021
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| Hasła przedmiotowe: | |
| Dostęp online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8011767/ https://ncbi.nlm.nih.gov/pubmed/33788888 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0248636 |
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