118. Machine Learning Approaches to Predicting Treatment Outcomes for Carbapenem-Resistant Enterobacterales in a Region with High Prevalence of Non-Carbapenemase Producers

BACKGROUND: Carbapenem-resistant Enterobacterales are a growing threat globally. Early detection of CRE is necessary for appropriate treatment and infection control measures. Many hospital labs can test for carbapenemase production; however, in some regions, including South Texas, the majority of CR...

Descripción completa

Detalles Bibliográficos
Autores principales: Black, Cody A, Aguilar, Samantha, Bandy, Sarah, Gawrys, Gerard, Dallas, Steven, So, Wonhee, Benavides, Raymond, Betrabet, Neha, Diaz, Catherine, Anderson, Audrey, Lee, Grace
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Oral Abstracts
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8644127/
http://dx.doi.org/10.1093/ofid/ofab466.118

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8644127/
http://dx.doi.org/10.1093/ofid/ofab466.118

Ejemplares similares