Development of machine learning models for the detection of surgical site infections following total hip and knee arthroplasty: a multicenter cohort study

BACKGROUND: Population based surveillance of surgical site infections (SSIs) requires precise case-finding strategies. We sought to develop and validate machine learning models to automate the process of complex (deep incisional/organ space) SSIs case detection. METHODS: This retrospective cohort st...

Descripción completa

Detalles Bibliográficos
Autores principales: Wu, Guosong, Cheligeer, Cheligeer, Southern, Danielle A., Martin, Elliot A., Xu, Yuan, Leal, Jenine, Ellison, Jennifer, Bush, Kathryn, Williamson, Tyler, Quan, Hude, Eastwood, Cathy A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10474760/
https://www.ncbi.nlm.nih.gov/pubmed/37658409
http://dx.doi.org/10.1186/s13756-023-01294-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10474760/
https://www.ncbi.nlm.nih.gov/pubmed/37658409
http://dx.doi.org/10.1186/s13756-023-01294-0

Ejemplares similares