Predicting 24-hour intraocular pressure peaks and averages with machine learning
CORRECTION article
Corrigendum: Predicting 24-hour intraocular pressure peaks and averages with machine learning
Provisionally accepted- 1 Department of Ophthalmology, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China
- 2 Software Engineering, Shenzhen Yishi Huolala Technology Company Limited, Shenzhen, China
- 3 Department of Ophthalmology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China, Shanghai, China
- 4 Department of Ophthalmology, Tongji Eye Institute, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China, Shanghai, China
In the published article, there was an error in “Predicting 24-hour intraocular pressure peaks and averages with machine learning” as published. I am writing to request a correction regarding our paper titled Predicting 24-hour intraocular pressure peaks and averages with machine learning (https://doi.org/10.3389/fmed.2024.1459629), published on October 7. During the final confirmation process, we updated the term “gender” to “sex” in the manuscript; however, we regrettably overlooked this change in Figure 4.
Keywords: Intraocular Pressure, 24-hour, Measurement, nocturnal, machine learning, Glaucoma
Received: 19 Oct 2024; Accepted: 29 Oct 2024.
Copyright: © 2024 Ranran, Lei, Yujie, Yiping, Wang, Xiaomei, Danping, Li, Bi and Haohao. 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) or licensor 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:
Zhu Haohao, Department of Ophthalmology, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China
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