
==== Front
Front Endocrinol (Lausanne)
Front Endocrinol (Lausanne)
Front. Endocrinol.
Frontiers in Endocrinology
1664-2392
Frontiers Media S.A.

10.3389/fendo.2024.1466012
Endocrinology
Correction
Corrigendum: Improving the diagnostic performance of inexperienced readers for thyroid nodules through digital self-learning and artificial intelligence assistance
Lee Si Eun 1

Kim Hye Jung 2 *
Jung Hae Kyoung 3
Jung Jin Hyang 4
Jeon Jae-Han 5
Lee Jin Hee 6
Hong Hanpyo 1
Lee Eun Jung 7
Kim Daham 8

Kwak Jin Young 9 *

1 Department of Radiology, Yongin Severance Hospital, College of Medicine, Yonsei University, Yongin-si, Republic of Korea
2 Department of Radiology, Kyungpook National University Chilgok Hospital, Daegu, Republic of Korea
3 Department of Radiology, CHA University Bundang Medical Center, Seongnam-si, Republic of Korea
4 Department of Surgery, Kyungpook National University Chilgok Hospital, Daegu, Republic of Korea
5 Department of Endocrinology, Kyungpook National University Chilgok Hospital, Daegu, Republic of Korea
6 Department of Radiology, Keimyung University Dongsan Hospital, Daegu, Republic of Korea
7 Department of Computational Science and Engineering, Yonsei University, Seoul, Republic of Korea
8 Department of Endocrinology, College of Medicine, Yonsei University, Seoul, Republic of Korea
9 Department of Radiology, College of Medicine, Yonsei University, Seoul, Republic of Korea
Approved by: Frontiers Editorial Office, Frontiers Media SA, Switzerland

*Correspondence: Hye Jung Kim, ant637@knuh.kr; Jin Young Kwak, docjin@yuhs.ac
02 9 2024
2024
02 9 2024
15 146601217 7 2024
21 8 2024
Copyright © 2024 Lee, Kim, Jung, Jung, Jeon, Lee, Hong, Lee, Kim and Kwak
2024
Lee, Kim, Jung, Jung, Jeon, Lee, Hong, Lee, Kim and Kwak
https://creativecommons.org/licenses/by/4.0/ 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.
A Corrigendum on Improving the diagnostic performance of inexperienced readers for thyroid nodules through digital self-learning and artificial intelligence assistance By Lee SE, Kim HJ, Jung HK, Jung JH, Jeon J-H, Lee JH, Hong H, Lee EJ, Kim D and Kwak JY (2024). Front. Endocrinol. 15:1372397. doi: 10.3389/fendo.2024.1372397 thyroid cancer
artificial intelligence
ultrasound
learning
digital learning
Ministry of Science and ICT, South Korea 10.13039/501100014188 section-in-acceptanceThyroid Endocrinology
==== Body
pmcIn the published article, an author name was incorrectly written as Jing Hyang Jung. The correct spelling is Jin Hyang Jung.

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.
