Cargando…
Mortality prediction in ICU Using a Stacked Ensemble Model
Artificial intelligence (AI) technology has huge scope in developing models to predict the survival rate of critically ill patients in the intensive care unit (ICU). The availability of electronic clinical data has led to the widespread use of various machine learning approaches in this field. Innov...
Autores principales: | Ren, Na, Zhao, Xin, Zhang, Xin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9722283/ https://www.ncbi.nlm.nih.gov/pubmed/36479315 http://dx.doi.org/10.1155/2022/3938492 |
Ejemplares similares
-
Applying an Improved Stacking Ensemble Model to Predict the Mortality of ICU Patients with Heart Failure
por: Chiu, Chih-Chou, et al.
Publicado: (2022) -
Efficacy prediction of noninvasive ventilation failure based on the stacking ensemble algorithm and autoencoder
por: Liang, Na, et al.
Publicado: (2022) -
Stacking ensemble learning model to predict 6-month mortality in ischemic stroke patients
por: Hwangbo, Lee, et al.
Publicado: (2022) -
An Empirical Model to Predict the Diabetic Positive Using Stacked Ensemble Approach
por: R., Sivashankari, et al.
Publicado: (2022) -
Stack-VTP: prediction of vesicle transport proteins based on stacked ensemble classifier and evolutionary information
por: Chen, Yu, et al.
Publicado: (2023)