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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 (...
Autores principales: | Shim, Jae-Geum, Lee, Eun Kyung, Oh, Eun Jung, Cho, Eun-Ah, Park, Jiyeon, Lee, Jun-Ho, Ahn, Jin Hee |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
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 |
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