Predicting the risk of inappropriate depth of endotracheal intubation in pediatric patients using machine learning approaches

Endotracheal tube (ET) misplacement is common in pediatric patients, which can lead to the serious complication. It would be helpful if there is an easy-to-use tool to predict the optimal ET depth considering in each patient’s characteristics. Therefore, we plan to develop a novel machine learning (...

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Detalles Bibliográficos
Autores principales: Shim, Jae-Geum, Lee, Eun Kyung, Oh, Eun Jung, Cho, Eun-Ah, Park, Jiyeon, Lee, Jun-Ho, Ahn, Jin Hee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10057688/
https://www.ncbi.nlm.nih.gov/pubmed/36991074
http://dx.doi.org/10.1038/s41598-023-32122-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10057688/
https://www.ncbi.nlm.nih.gov/pubmed/36991074
http://dx.doi.org/10.1038/s41598-023-32122-5

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