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. 2024 May 9;24:142. doi: 10.1186/s12893-024-02427-x

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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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 6 — Web calculator interface and SHAP value analysis for OVCF risk prediction. The interface shows input fields for patient parameters relevant to the prediction of new fractures after PVP in patients with OVCF. After entering these parameters and clicking "Predict," the model calculates the probability of a fracture occurring and displays it along with a graph of SHAP values to the right.The SHAP value graph illustrates the contribution of each parameter to the model's prediction, with a positive SHAP value indicating an increased risk of a fracture and a negative SHAP value indicating a decreased risk of a fracture. The length of each bar indicates the level of influence of the feature, and the colour indicates the direction of influence (purple for positive influence, yellow for negative influence)