Efficacy prediction of noninvasive ventilation failure based on the stacking ensemble algorithm and autoencoder

BACKGROUND: Early prediction of noninvasive ventilation failure is of great significance for critically ill ICU patients to escalate or change treatment. Because clinically collected data are highly time-series correlated and have imbalanced classes, it is difficult to accurately predict the efficac...

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Detalles Bibliográficos
Autores principales: Liang, Na, Wang, Chengliang, Duan, Jun, Xie, Xin, Wang, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8805397/
https://www.ncbi.nlm.nih.gov/pubmed/35101003
http://dx.doi.org/10.1186/s12911-022-01767-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8805397/
https://www.ncbi.nlm.nih.gov/pubmed/35101003
http://dx.doi.org/10.1186/s12911-022-01767-z

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