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. 2024 May 21;14:11588. doi: 10.1038/s41598-024-62076-1

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© The Author(s) 2024

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Performance analysis of ScoreDFUNet. (A) F1-score Performance: Illustrates the F1-score performance of the Clf4DFU model, showcasing its ability to achieve a balanced trade-off between precision and recall in diabetic foot ulcer classification. (B) ROC Curve: Presents the receiver operating characteristic (ROC) curve, highlighting the model's effectiveness in distinguishing between different lesion categories. (C) Confusion Matrix: Provides a comprehensive breakdown of the model's stratification results, facilitating a detailed assessment of its accuracy and potential areas for improvement. (D–F) Feature Influence Analysis: Offers both qualitative and quantitative saliency analysis, emphasizing the significance of various diabetic foot ulcer features in influencing the model's predictions. (G) Relevance Colorbar.