Editorial Note: Machine learning model for predicting the optimal depth of tracheal tube insertion in pediatric patients: A retrospective cohort study

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Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-01-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12143554/?tool=EBI
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collection DOAJ
format Article
id doaj-art-7ba345e72c7b4b44a531aeeb6d05c441
institution OA Journals
issn 1932-6203
language English
publishDate 2025-01-01
publisher Public Library of Science (PLoS)
record_format Article
series PLoS ONE
spelling doaj-art-7ba345e72c7b4b44a531aeeb6d05c4412025-08-20T02:08:46ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01206Editorial Note: Machine learning model for predicting the optimal depth of tracheal tube insertion in pediatric patients: A retrospective cohort studyhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC12143554/?tool=EBI
spellingShingle Editorial Note: Machine learning model for predicting the optimal depth of tracheal tube insertion in pediatric patients: A retrospective cohort study
PLoS ONE
title Editorial Note: Machine learning model for predicting the optimal depth of tracheal tube insertion in pediatric patients: A retrospective cohort study
title_full Editorial Note: Machine learning model for predicting the optimal depth of tracheal tube insertion in pediatric patients: A retrospective cohort study
title_fullStr Editorial Note: Machine learning model for predicting the optimal depth of tracheal tube insertion in pediatric patients: A retrospective cohort study
title_full_unstemmed Editorial Note: Machine learning model for predicting the optimal depth of tracheal tube insertion in pediatric patients: A retrospective cohort study
title_short Editorial Note: Machine learning model for predicting the optimal depth of tracheal tube insertion in pediatric patients: A retrospective cohort study
title_sort editorial note machine learning model for predicting the optimal depth of tracheal tube insertion in pediatric patients a retrospective cohort study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12143554/?tool=EBI