Cargando…
Improving Prediction Accuracy of “Central Line-Associated Blood Stream Infections” Using Data Mining Models
Prediction of nosocomial infections among patients is an important part of clinical surveillance programs to enable the related personnel to take preventive actions in advance. Designing a clinical surveillance program with capability of predicting nosocomial infections is a challenging task due to...
Autores principales: | Noaman, Amin Y., Nadeem, Farrukh, Ragab, Abdul Hamid M., Jamjoom, Arwa, Al-Abdullah, Nabeela, Nasir, Mahreen, Ali, Anser G. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5632447/ https://www.ncbi.nlm.nih.gov/pubmed/29085836 http://dx.doi.org/10.1155/2017/3292849 |
Ejemplares similares
-
WMSS: A Web-Based Multitiered Surveillance System for Predicting CLABSI
por: Noaman, Amin Y., et al.
Publicado: (2018) -
Central and peripheral venous lines-associated blood stream infections in the critically ill surgical patients
por: Ugas, Mohamed Ali, et al.
Publicado: (2012) -
Stream data mining
por: Rutkowski, Leszek, et al.
Publicado: (2019) -
2300. Molecular Epidemiology of Carbapenem-Resistant Klebsiella pneumoniae (CRKP) Causing Central Line Associated Blood Stream Infections (CLABSI) in Three ICU Units in Egypt
por: Kholy, Amany El, et al.
Publicado: (2018) -
705 Reduction in Central Line Associated Blood Stream Infection Rate with a Central Line Change-Over Protocol
por: Hollowell, Jamie L, et al.
Publicado: (2022)