Rule-Based Models for Risk Estimation and Analysis of In-hospital Mortality in Emergency and Critical Care
We propose a novel method that uses associative classification and odds ratios to predict in-hospital mortality in emergency and critical care. Manual mortality risk scores have previously been used to assess the care needed for each patient and their need for palliative measures. Automated approach...
Guardado en:
Autores principales: | Oliver Haas, Andreas Maier, Eva Rothgang |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/1eeed6ee220448a6aad391d4e27c93b8 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Machine Learning-Based HIV Risk Estimation Using Incidence Rate Ratios
por: Oliver Haas, et al.
Publicado: (2021) -
Odds ratio: aspectos teóricos y prácticos
por: Cerda,Jaime, et al.
Publicado: (2013) -
TESTING ASSORTATIVE MATING: EVIDENCE FROM ARGENTINA
por: GABRIELLI,MARIA FLORENCIA, et al.
Publicado: (2017) -
Machine learning for identification of dental implant systems based on shape – A descriptive study
por: Veena Basappa Benakatti, et al.
Publicado: (2021) -
Características y evolución de los pacientes que ingresan a una Unidad de Cuidados Intensivos de un hospital público
por: Ruiz,Carolina, et al.
Publicado: (2016)