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Articles Published Processes
8/24/2026 6:01:13 AM | Browse: 0 | Download: 0
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Received |
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2026-04-17 10:06 |
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Peer-Review Started |
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2026-04-17 10:06 |
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First Decision by Editorial Office Director |
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2026-05-07 09:22 |
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Return for Revision |
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2026-05-07 09:22 |
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Revised |
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2026-05-22 04:03 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-06-15 02:42 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-06-15 06:03 |
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Articles in Press |
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2026-06-15 06:03 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-07-17 00:45 |
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Publish the Manuscript Online |
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2026-08-24 06:01 |
| ISSN |
2220-3206 (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 |
©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| 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 |
Psychology |
| Manuscript Type |
Retrospective Study |
| Article Title |
Efficacy of a machine learning model integrating clinical-psychosocial factors in predicting posttraumatic bone nonunion and bone defects
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Fei-Fan Luan, Jia-Yi Chen, Yu-Zhong Zheng, Min-Hua Hu, Feng Huang and Chen-Xiao Zheng |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Chen-Xiao Zheng, PhD, Zhongshan Hospital of Traditional Chinese Medicine Affliated to Guangzhou University of Traditional Chinese Medicine, The Tenth Clinical Medical College of Guangzhou University of Traditional Chinese Medicine, No.3 Kangxin Road, West District, Zhongshan 528400, Guangdong Province, China. cuokoo1973@163.com |
| Key Words |
Bone nonunion; Machine learning; Psychosocial factors; Risk prediction; Decision curve analysis |
| Core Tip |
In summary, the integrated model developed in this study demonstrates favorable discriminative ability (operating characteristic curve = 0.888 in external validation) and potential clinical utility for nonunion risk prediction, although further validation is needed. Importantly, our findings highlight the significant contribution of psychosocial factors - particularly anxiety, depression, and social support - to bone healing. These results provide strong evidence for promoting the deep integration of the “bio‑psycho‑social” medical model into routine orthopedic clinical practice, thereby facilitating more individualized and holistic patient management. |
| Publish Date |
2026-08-24 06:01 |
| Citation |
Luan FF, Chen JY, Zheng YZ, Hu MH, Huang F, Zheng CX. Efficacy of a machine learning model integrating clinical-psychosocial factors in predicting posttraumatic bone nonunion and bone defects. World J Psychiatry 2026; 16(9): 119455
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| URL |
https://www.wjgnet.com/2220-3206/full/v16/i9/119455.htm |
| DOI |
https://doi.org/10.5498/wjp.119455 |
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