Cargando…
Machine learning for predicting successful extubation in patients receiving mechanical ventilation
Ventilator liberation is one of the most critical decisions in the intensive care unit; however, prediction of extubation failure is difficult, and the proportion thereof remains high. Machine learning can potentially provide a breakthrough in the prediction of extubation success. A total of seven s...
Autores principales: | Igarashi, Yutaka, Ogawa, Kei, Nishimura, Kan, Osawa, Shuichiro, Ohwada, Hayato, Yokobori, Shoji |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9403066/ https://www.ncbi.nlm.nih.gov/pubmed/36035403 http://dx.doi.org/10.3389/fmed.2022.961252 |
Ejemplares similares
-
Developing a machine-learning model for real-time prediction of successful extubation in mechanically ventilated patients using time-series ventilator-derived parameters
por: Huang, Kuo-Yang, et al.
Publicado: (2023) -
Development and Validation of a Machine-Learning Model for Prediction of Extubation Failure in Intensive Care Units
por: Zhao, Qin-Yu, et al.
Publicado: (2021) -
The Contribution of Chest X-Ray to Predict Extubation Failure in Mechanically Ventilated Patients Using Machine Learning-Based Algorithms
por: Fukuchi, Kiyoyasu, et al.
Publicado: (2022) -
No association between thickening fraction of the diaphragm and extubation success in ventilated children
por: Duyndam, Anita, et al.
Publicado: (2023) -
Ventilator management and risk of air leak syndrome in patients with SARS-CoV-2 pneumonia: a single-center, retrospective, observational study
por: Miyake, Nodoka, et al.
Publicado: (2023)