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CORRECTION article

Front. Med., 08 November 2024
Sec. Ophthalmology
Volume 11 - 2024 | https://doi.org/10.3389/fmed.2024.1513862

Corrigendum: Predicting 24-hour intraocular pressure peaks and averages with machine learning

This article is a correction to:

  1. Predicting 24-hour intraocular pressure peaks and averages with machine learning

    1. Read original article
\nRanran ChenRanran Chen1Jinming LeiJinming Lei2Yujie LiaoYujie Liao1Yiping JinYiping Jin1Xue WangXue Wang3Xiaomei LiXiaomei Li1Danping WuDanping Wu1Hong LiHong Li1Yanlong Bi Yanlong Bi4*Haohao Zhu Haohao Zhu1*
  • 1Department of Ophthalmology, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China
  • 2Software Engineering, Shenzhen Yishi Huolala Technology Company Limited, Shenzhen, China
  • 3Department of Ophthalmology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
  • 4Department of Ophthalmology, Tongji Eye Institute, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China

A Corrigendum on
Predicting 24-hour intraocular pressure peaks and averages with machine learning

by Chen, R., Lei, J., Liao, Y., Jin, Y., Wang, X., Li, X., Wu, D., Li, H., Bi, Y., and Zhu, H. (2024). Front. Med. 11:1459629. doi: 10.3389/fmed.2024.1459629

In the published article, there was an error in Figure 4. During the final confirmation process, we updated the term “gender” to “sex” in the manuscript; however, we regrettably overlooked this change in Figure 4. The corrected Figure 4 and its caption appear below.

Figure 4
www.frontiersin.org

Figure 4. SHAP value analysis for peak and average IOP prediction models. (A) SHAP values for peak IOP prediction model. (B) SHAP values for average IOP prediction model.

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Keywords: intraocular pressure, 24-hour, measurement, nocturnal, machine learning, glaucoma

Citation: Chen R, Lei J, Liao Y, Jin Y, Wang X, Li X, Wu D, Li H, Bi Y and Zhu H (2024) Corrigendum: Predicting 24-hour intraocular pressure peaks and averages with machine learning. Front. Med. 11:1513862. doi: 10.3389/fmed.2024.1513862

Received: 19 October 2024; Accepted: 29 October 2024;
Published: 08 November 2024.

Edited and reviewed by: Flora Hui, Centre for Eye Research Australia, Australia

Copyright © 2024 Chen, Lei, Liao, Jin, Wang, Li, Wu, Li, Bi and Zhu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Yanlong Bi, biyanlong@tongji.edu.cn; Haohao Zhu, zhuhaohao@fudan.edu.cn

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.