Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57654, first published .
Correction: A Novel Convolutional Neural Network for the Diagnosis and Classification of Rosacea: Usability Study

Correction: A Novel Convolutional Neural Network for the Diagnosis and Classification of Rosacea: Usability Study

Correction: A Novel Convolutional Neural Network for the Diagnosis and Classification of Rosacea: Usability Study

Corrigenda and Addenda

1Department of Dermatology, Xiangya Hospital of Central South University, Changsha, China

2Hunan Key Laboratory of Aging Biology, Xiangya Hospital of Central South University, Changsha, China

3aetherAI, Co Ltd, Taipei, Taiwan, China

4National Clinical Research Center for Geriatric Disorders, Xiangya Hospital of Central South University, Changsha, China

5Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, Changsha, China

*these authors contributed equally

Corresponding Author:

Ji Li, MD, PhD

Department of Dermatology

Xiangya Hospital of Central South University

87 Xiangya Rd.

Changsha, 410008

China

Phone: 86 073189753406

Email: liji_xy@csu.edu.cn



In “A Novel Convolutional Neural Network for the Diagnosis and Classification of Rosacea: Usability Study” (JMIR Med Inform 2021;9(3):e23415) the authors made one addition.

An “Acknowledgments” section has been added that reads as follows:

This work was supported by The Educational Science and Planning Project of Hunan Province (XTK20BGD008).

The correction will appear in the online version of the paper on the JMIR Publications website on March 8, 2024, together with the publication of this correction notice. Because this was made after submission to PubMed, PubMed Central, and other full-text repositories, the corrected article has also been resubmitted to those repositories.

This is a non–peer-reviewed article. submitted 26.02.24; accepted 27.02.24; published 08.03.24.

Copyright

©Zhixiang Zhao, Che-Ming Wu, Shuping Zhang, Fanping He, Fangfen Liu, Ben Wang, Yingxue Huang, Wei Shi, Dan Jian, Hongfu Xie, Chao-Yuan Yeh, Ji Li. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 08.03.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.