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Articles Published Processes
1/26/2026 6:06:22 AM | Browse: 1 | Download: 0
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Received |
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2025-10-20 02:11 |
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Peer-Review Started |
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2025-10-20 02:11 |
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First Decision by Editorial Office Director |
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2025-11-06 09:07 |
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Return for Revision |
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2025-11-06 09:07 |
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Revised |
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2025-11-12 20:03 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2025-12-15 02:40 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2025-12-15 07:03 |
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Articles in Press |
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2025-12-15 07:03 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-01-14 08:11 |
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Publish the Manuscript Online |
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2026-01-26 06:06 |
| ISSN |
1949-8470 (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) 2025. 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 |
Magnetic resonance imaging-based deep-learning radiomics score for survival prediction and risk stratification in pediatric hepatoblastoma receiving surgical resection
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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 |
Yuan Li, Laboratory of Digestive Surgery, State Key Laboratory of Biotherapy and Cancer Center, Department of Pediatric Surgery, West China Hospital, Sichuan University, No. 37 Guoxue alley, Chengdu 6100000, Sichuan Province, China. l13258389785@126.com |
| Key Words |
Deep learning; Radiomics; Nomogram; Magnetic resonance imaging; Event-free survival; Hepatoblastoma |
| Core Tip |
In the present research, we generated a deep learning based radiomics score in the prediction of event-free survival for children with hepatoblastoma receiving surgical resection from multiple institutions, and developed an integrated clinical-deep learning nomogram based on widely accepted clinicopathologic predictors and the deep learning based radiomics score. The integrated nomogram showed great prediction performance for event-free survival with external validation, which might instruct therapeutic interventions. Further research is needed to validate the risk identification performance for improving clinical practicability and generality. |
| Publish Date |
2026-01-26 06:06 |
| Citation |
Yang YH, Li Y. Magnetic resonance imaging-based deep-learning radiomics score for survival prediction and risk stratification in pediatric hepatoblastoma receiving surgical resection. World J Radiol 2026; 18(1): 115503 |
| URL |
https://www.wjgnet.com/1949-8470/full/v18/i1/115503.htm |
| DOI |
https://dx.doi.org/10.4329/wjr.v18.i1.115503 |
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