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Publication Name World Journal of Diabetes
Manuscript ID 104789
Country China
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
Manuscript Source Unsolicited Manuscript
All Author List Lei Gao, Zi-Xuan Liu and Jiang-Ning Wang
Funding Agency and Grant Number
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.
Citation 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. World J Diabetes 2025; In press
Received
2025-01-02 09:48
Peer-Review Started
2025-01-03 08:59
To Make the First Decision
Return for Revision
2025-04-09 01:25
Revised
2025-04-22 03:21
Second Decision
2025-05-15 08:36
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief
2025-06-13 07:56
Articles in Press
2025-06-13 07:56
Publication Fee Transferred
2025-04-23 08:39
Edit the Manuscript by Language Editor
Typeset the Manuscript
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.
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