Clostridioides difficile infection surveillance in intensive care units and oncology wards using machine learning

OBJECTIVE: Screening individuals admitted to the hospital for Clostridioides difficile presents opportunities to limit transmission and hospital-onset C. difficile infection (HO-CDI). However, detection from rectal swabs is resource intensive. In contrast, machine learning (ML) models may accurately...

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Detalles Bibliográficos
Autores principales: Ötleş, Erkin, Balczewski, Emily A., Keidan, Micah, Oh, Jeeheh, Patel, Alieysa, Young, Vincent B., Rao, Krishna, Wiens, Jenna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10665879/
https://www.ncbi.nlm.nih.gov/pubmed/37088695
http://dx.doi.org/10.1017/ice.2023.54

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10665879/
https://www.ncbi.nlm.nih.gov/pubmed/37088695
http://dx.doi.org/10.1017/ice.2023.54

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