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Articles Published Processes
3/23/2026 8:21:11 AM | Browse: 19 | Download: 53
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Received |
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2025-09-28 00:38 |
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Peer-Review Started |
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2025-09-28 00:38 |
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First Decision by Editorial Office Director |
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2025-10-17 07:37 |
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Return for Revision |
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2025-10-17 07:37 |
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Revised |
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2025-10-21 20:53 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-01-28 02:41 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-01-28 09:42 |
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Articles in Press |
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2026-01-28 09:42 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-03-12 00:36 |
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Publish the Manuscript Online |
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2026-03-23 08:21 |
| ISSN |
2218-4333 (online) |
| Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2026. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Pediatrics |
| Manuscript Type |
Retrospective Cohort Study |
| Article Title |
Deep learning radiomic analysis in the prediction of MYCN status and survival outcome in children with neuroblastoma
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Yu-Han Yang and Yuan Li |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Yu-Han Yang, MD, West China Hospital, Sichuan University, No.17 People's South Road, Chengdu 610041, Sichuan Province, China. yyh_1023@163.com |
| Key Words |
Neuroblastoma; MYCN amplification; Deep learning; Radiomics; Computed tomography; Event-free survival |
| Core Tip |
We constructed a deep learning (DL)-based radiomics signature on computed tomography, which had the ability to identify MYCN amplification in neuroblastoma. Integrating the DL-based radiomics signature and clinical predictors, the nomogram model showed improvement in the prediction of MYCN amplification in neuroblastomas. The DL-based radiomics signature was found to be associated with disease-specific events of neuroblastomas significantly after radical resection. |
| Publish Date |
2026-03-23 08:21 |
| Citation |
Yang YH, Li Y. Deep learning radiomic analysis in the prediction of MYCN status and survival outcome in children with neuroblastoma. World J Clin Oncol 2026; 17(3): 114744 |
| URL |
https://www.wjgnet.com/2218-4333/full/v17/i3/114744.htm |
| DOI |
https://dx.doi.org/10.5306/wjco.v17.i3.114744 |
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