Explainable machine learning model for predicting minor amputation in diabetic foot ulcers

doi:10.4239/wjd.124921

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Publication Name

World Journal of Diabetes

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1948-9358

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Retrospective Cohort Study

Copyright: ©Author(s) 2026. 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.

World J Diabetes. Nov 15, 2026; 17(11): 124921
Published online Nov 15, 2026. doi: 10.4239/wjd.124921

Table 5 Predictive performance evaluation of the random forest model

Model	Dataset	AUC (95%CI)	Sensitivity (95%CI)	Specificity (95%CI)	F1 score (95%CI)¹
RF	Train	0.844 (0.810-0.878)	0.747 (0.689-0.803)	0.761 (0.708-0.811)	0.737 (0.690-0.782)
RF	Validation	0.766 (0.700-0.828)	0.628 (0.529-0.722)	0.703 (0.618-0.788)	0.633 (0.551-0.710)

¹The F1 score represents the harmonic mean of precision and recall, calculated as 2 × (precision × recall)/(precision + recall). This metric evaluates binary classification performance and fits data with mild imbalance between two groups.

AUC: Area under the receiver operating characteristic curve; F1 score: F-measure (harmonic mean of precision and recall); RF: Random forest.

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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; 17(11): 124921
URL: https://www.wjgnet.com/1948-9358/full/v17/i11/124921.htm
DOI: https://dx.doi.org/10.4239/wjd.124921

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; 17(11): 124921 [DOI: 10.4239/wjd.124921]

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