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Articles Published Processes
7/15/2025 8:26:33 AM | Browse: 8 | Download: 49
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Received |
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2025-01-02 09:48 |
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Peer-Review Started |
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2025-01-03 08:59 |
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To Make the First Decision |
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Return for Revision |
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2025-04-09 01:25 |
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Revised |
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2025-04-22 03:21 |
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Second Decision |
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2025-05-15 08:36 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2025-06-13 07:56 |
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Articles in Press |
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2025-06-13 07:56 |
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Publication Fee Transferred |
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2025-04-23 08:39 |
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Edit the Manuscript by Language Editor |
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2025-06-17 20:06 |
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Typeset the Manuscript |
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2025-07-01 03:19 |
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Publish the Manuscript Online |
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2025-07-15 08:26 |
| ISSN |
1948-9358 (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 |
Computer Science, Artificial Intelligence |
| Manuscript Type |
Retrospective Study |
| Article Title |
Predictive model and risk analysis for outcomes in diabetic foot ulcer using eXtreme Gradient Boosting algorithm and SHapley Additive exPlanation
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Lei Gao, Zi-Xuan Liu and Jiang-Ning Wang |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Jiang-Ning Wang, Chief Physician, MD, Department of Orthopedics Surgery, Beijing Shijitan Hospital Affiliated to Capital Medical University, No. 10 Tieyi Road, Yangfangdian, Haidian District, Beijing 100038, China. wangjn@bjsjth.cn |
| Key Words |
Diabetic foot ulcer; Amputation stratification; Clinical risk prediction; eXtreme Gradient Boosting; Shapley additive explanation; Machine learning |
| Core Tip |
This study developed and validated an eXtreme Gradient Boosting-based predictive model for stratifying amputation risk in patients with diabetic foot ulcers. By integrating 29 clinical variables and applying Shapley additive explanation for interpretability, the model achieved high predictive accuracy, especially for major amputations (area under the curve = 0.977). Key predictors included Wagner grade, albumin, infection markers, and vascular intervention. The model enables early identification of high-risk patients and supports individualized treatment decisions, offering a clinically interpretable tool for improving diabetic foot management. |
| Publish Date |
2025-07-15 08:26 |
| Citation |
<p>Gao L, Liu ZX, Wang JN. Predictive model and risk analysis for outcomes in diabetic foot ulcer using eXtreme Gradient Boosting algorithm and SHapley Additive exPlanation. <i>World J Diabetes</i> 2025; 16(7): 104789</p> |
| URL |
https://www.wjgnet.com/1948-9358/full/v16/i7/104789.htm |
| DOI |
https://dx.doi.org/10.4239/wjd.v16.i7.104789 |
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