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...

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Detalles Bibliográficos
Autores principales: Møller, Jens Kjølseth, Sørensen, Martin, Hardahl, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8011767/
https://www.ncbi.nlm.nih.gov/pubmed/33788888
http://dx.doi.org/10.1371/journal.pone.0248636

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8011767/
https://www.ncbi.nlm.nih.gov/pubmed/33788888
http://dx.doi.org/10.1371/journal.pone.0248636

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