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Articles Published Processes
9/2/2026 6:35:30 AM | Browse: 1 | Download: 0
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Received |
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2025-11-21 08:01 |
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Peer-Review Started |
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2025-11-21 08:02 |
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First Decision by Editorial Office Director |
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2025-12-02 08:09 |
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Return for Revision |
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2025-12-02 08:09 |
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Revised |
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2025-12-03 17:24 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-02-02 02:45 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-02-02 14:36 |
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Articles in Press |
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2026-02-02 14:36 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-03-13 01:55 |
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Publish the Manuscript Online |
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2026-09-02 06:35 |
| ISSN |
2644-3228 (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: https://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 |
Orthopedics |
| Manuscript Type |
Retrospective Cohort Study |
| Article Title |
Magnetic resonance imaging-based deep learning model for prediction of the neoadjuvant chemotherapy response and survival prognosis in adolescents with osteosarcoma
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Yu-Han Yang |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Yu-Han Yang, West China School of Medicine, Sichuan University, No. 17 People's South Road, Chengdu 6100041, Sichuan Province, China. yyh_1023@163.com |
| Key Words |
Osteosarcoma; Magnetic resonance imaging; Neoadjuvant chemotherapy; Deep learning; Convolutional neural network |
| Core Tip |
We developed and externally validated prediction models for histopathological diagnosis of resectable bone sarcomas using radiological features derived from both deep learning and handcrafted radiomics approaches. To our knowledge, this is the first study using pre-trained convolutional neural networks via transfer learning method to identify osteosarcoma and chondrosarcoma and predict long-term survival outcomes based on T1 and T2 magnetic resonance imaging images. |
| Publish Date |
2026-09-02 06:35 |
| Citation |
Yang YH. Magnetic resonance imaging-based deep learning model for prediction of the neoadjuvant chemotherapy response and survival prognosis in adolescents with osteosarcoma. Artif Intell Cancer 2026; 7(1): 116460
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| URL |
https://www.wjgnet.com/2644-3228/full/v7/i1/116460.htm |
| DOI |
https://doi.org/10.35713/aic.v7.i1.116460 |
Copyright © 1993-2026 Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA. All rights reserved, including rights relating to text and data mining, AI training, and similar technologies. For open-access content, the applicable copyright and licensing terms govern.
