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. 2023 Dec 19;13:22641. doi: 10.1038/s41598-023-50012-8

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© The Author(s) 2023

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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SHAP feature importance of the best prediction models for each task (a–e). For every feature, negative and positive average contributions are depicted separately, in bluish and reddish hues, respectively. (a) mRS > 2, (b) mRS-difference > 1, (c) permanent nND, (d) transient nND, (e) GOS < 5. mRS = modified Rankin Scale, BMI = body mass index, nND = new neurological deficit, ADPKD = autosomal dominant polycystic kidney disease, GOS = Glasgow outcome scale.