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10/20/2026 9:42:41 AM | Browse: 14 | Download: 3
Publication Name World Journal of Diabetes
Manuscript ID 124921
DOI 10.4239/wjd.124921
Country China
Category Endocrinology & Metabolism
Manuscript Type Retrospective Cohort Study
Article Title Explainable machine learning model for predicting minor amputation in diabetic foot ulcers
Manuscript Source Unsolicited Manuscript
All Author List Zhong-Jing Yang, Jun-Yan Zhao, Shao-Cong Hu, Yi Chen, Yun-Fei Kang, Juan Li, Liang-Chen Wang, Hong-Mei Chen, Zu-Yuan Zhang, Cai-Zhe Yang and Di Zhu
Funding Agency and Grant Number
Funding Agency Grant Number
National Natural Science Foundation of China No. 82470389
Capital’s Funds for Health Improvement and Research No. 2024-4-5122
Young Talent Program of Air Force Medical Center No. 22BJQN005
Corresponding Author Di Zhu, Chief Physician, MD, Department of Endocrinology, Air Force Medical Center, No. 28 Fucheng Road, Beijing 100142, China. judy3481@163.com
Key Words Diabetic foot ulcers; Minor amputation; Clinical prediction model; Machine learning; C-reactive protein-albumin-lymphocyte index; SHapley Additive exPlanations
Core Tip This study developed and validated an explainable machine learning model to predict minor amputation within 3 months of admission in patients with diabetic foot ulcers. Among six compared algorithms, the random forest model performed best (validation area under the receiver operating characteristic curve = 0.766), identifying fibrinogen, pedal vessel calcification, albumin, and the C-reactive protein-albumin-lymphocyte index as independent predictors. SHapley Additive exPlanations analysis provided visual, patient-level interpretation of feature contributions. The model relies exclusively on routinely available laboratory and radiographic variables, offering a practical and objective tool for early risk stratification that may help clinicians identify high-risk diabetic foot ulcers patients and initiate timely targeted interventions.
Citation Yang ZJ, Zhao JY, Hu SC, Chen Y, Kang YF, Li J, Wang LC, Chen HM, Zhang ZY, Yang CZ, Zhu D. Explainable machine learning model for predicting minor amputation in diabetic foot ulcers. World J Diabetes 2026; In press
PDF 124921-in-press.pdf
Received
2026-06-29 01:35
Peer-Review Started
2026-07-07 10:03
First Decision by Editorial Office Director
Return for Revision
2026-07-20 08:53
Revised
2026-08-03 05:49
Publication Fee Transferred
2026-08-31 09:36
Second Decision by Editor
2026-10-05 08:18
Second Decision by Editor-in-Chief
2026-10-09 09:51
Final Decision by Editorial Office Director
2026-10-20 09:42
Articles in Press
2026-10-20 09:42
Edit the Manuscript by Language Editor
Typeset the Manuscript
ISSN 1948-9358 (online)
Open Access This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
Copyright ©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
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Publisher Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
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