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Prediction of respiratory failure risk in patients with pneumonia in the ICU using ensemble learning models

The aim of this study was to develop early prediction models for respiratory failure risk in patients with severe pneumonia using four ensemble learning algorithms: LightGBM, XGBoost, CatBoost, and random forest, and to compare the predictive performance of each model. In this study, we used the eIC...

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Detalles Bibliográficos
Autores principales: Lyu, Guanqi, Nakayama, Masaharu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10513189/
https://www.ncbi.nlm.nih.gov/pubmed/37733699
http://dx.doi.org/10.1371/journal.pone.0291711

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