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Editorial Note

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

  • The PLOS One Editors

The PLOS One Editors issue this Editorial Note to inform readers that after this article’s [1] publication, we identified potential competing interests between the authors and one or more of the peer reviewers. PLOS reviewed this matter and concluded that the article’s publication is supported based on expert input that was received during pre-publication peer review, including from individuals for whom there are no known competing interest issues.

Reference

  1. 1. Shim J-G, Ryu K-H, Lee SH, Cho E-A, Lee S, Ahn JH. Machine learning model for predicting the optimal depth of tracheal tube insertion in pediatric patients: a retrospective cohort study. PLoS One. 2021;16(9):e0257069. pmid:34473775

Citation: The PLOS One Editors (2025) Editorial Note: Machine learning model for predicting the optimal depth of tracheal tube insertion in pediatric patients: A retrospective cohort study. PLoS One 20(6): e0325971. https://doi.org/10.1371/journal.pone.0325971

Published: June 6, 2025

Copyright: © 2025 The PLOS One Editors. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.