This article is a correction to:
Radiomic Machine Learning and External Validation Based on 3.0 T mpMRI for Prediction of Intraductal Carcinoma of Prostate With Different Proportion
Ling Yang1†
Zhengyan Li1†Xu Liang2
Jingxu Xu3Yusen Cai3
Chencui Huang3Mengni Zhang4Jin Yao1*‡
Bin Song1*‡- 1Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- 2Department of Radiology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
- 3Department of Research Collaboration, R&D center, Beijing Deepwise & League of PHD Technology Co., Ltd., Beijing, China
- 4Department of Pathology, West China Hospital of Sichuan University, Chengdu, China
By Yang L, Li Z, Liang X, Xu J, Cai Y, Huang C, Zhang M, Yao J and Song B (2022) Front. Oncol. 12:934291. doi: 10.3389/fonc.2022.934291
In the published article, there was an error in the Funding statement for Science and Technology Support Program of Sichuan Province (No. 22NSFSC117). The correct Funding statement appears below.
FUNDING
This work was supported by the 1*3*5 Project for Disciplines of Excellence, West China Hospital, Sichuan University (No. ZY2017304), Science and Technology Support Program of Sichuan Province (No. 2022NSFSC0840) and the sky imaging research foundation (Z-2014-07-1912).
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
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Keywords: radiomics, machine learning, prostate cancer, intraductal carcinoma, multiparametric MRI
Citation: Yang L, Li Z, Liang X, Xu J, Cai Y, Huang C, Zhang M, Yao J and Song B (2024) Corrigendum: Radiomic machine learning and external validation based on 3.0T mpMRI for prediction of intraductal carcinoma of prostate with different proportion. Front. Oncol. 14:1401121. doi: 10.3389/fonc.2024.1401121
Received: 14 March 2024; Accepted: 18 March 2024;
Published: 03 April 2024.
Approved by:
Frontiers Editorial Office, Frontiers Media SA, SwitzerlandCopyright © 2024 Yang, Li, Liang, Xu, Cai, Huang, Zhang, Yao and Song. 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: Jin Yao, shelleyyao@163.com; Bin Song, songlab_radiology@163.com
†These authors have contributed equally to this work and share first authorship
‡These authors have contributed equally to this work