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Predictors for extubation failure in COVID-19 patients using a machine learning approach
INTRODUCTION: Determining the optimal timing for extubation can be challenging in the intensive care. In this study, we aim to identify predictors for extubation failure in critically ill patients with COVID-19. METHODS: We used highly granular data from 3464 adult critically ill COVID patients in t...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8711075/ https://www.ncbi.nlm.nih.gov/pubmed/34961537 http://dx.doi.org/10.1186/s13054-021-03864-3 |