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Articles Published Processes
9/24/2025 9:02:03 AM | Browse: 72 | Download: 14
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Received |
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2025-04-02 02:53 |
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Peer-Review Started |
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2025-04-02 02:53 |
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To Make the First Decision |
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Return for Revision |
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2025-04-20 05:01 |
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Revised |
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2025-05-14 09:43 |
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Second Decision |
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2025-07-31 02:40 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2025-07-31 06:38 |
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Articles in Press |
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2025-07-31 06:38 |
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Publication Fee Transferred |
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2025-05-15 16:13 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2025-09-04 06:01 |
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Publish the Manuscript Online |
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2025-09-24 09:02 |
| ISSN |
1948-9366 (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) 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 |
Gastroenterology & Hepatology |
| Manuscript Type |
Retrospective Study |
| Article Title |
Prediction of parastomal hernia in patients undergoing preventive ostomy after rectal cancer resection using machine learning
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Wang-Shuo Yang, Yang Su, Yan-Qi Li, Jun-Bo Hu, Meng-Die Liu and Lu Liu |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Yang Su, Full Professor, Department of Thoracic Surgery, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, China. yangsueinfo@163.com |
| Key Words |
Machine learning; Rectal cancer; Parastomal Hernia; Shapley additive explanation algorithms; Predictive model |
| Core Tip |
This research proposed and validated a predictive model based on machine learning techniques to assess the risk of parastomal hernia following prophylactic ostomy in individuals with rectal cancer. Among multiple algorithms, the random forest (RF) model achieved the best performance. Shapley additive explanations identified tumor distance from the anal verge, body mass index, and preoperative hypertension as key predictors. An online risk prediction tool based on the RF model has been created to support early screening and individualized postoperative management, offering practical value for clinical decision-making. |
| Publish Date |
2025-09-24 09:02 |
| Citation |
<p>Yang WS, Su Y, Li YQ, Hu JB, Liu MD, Liu L. Prediction of parastomal hernia in patients undergoing preventive ostomy after rectal cancer resection using machine learning. <i>World J Gastrointest Surg</i> 2025; 17(9): 107977</p> |
| URL |
https://www.wjgnet.com/1948-9366/full/v17/i9/107977.htm |
| DOI |
https://dx.doi.org/10.4240/wjgs.v17.i9.107977 |
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