Constructing a machine learning model for systemic infection after kidney stone surgery based on CT values

Abstract This study aims to develop a machine learning model utilizing Computed Tomography (CT) values to predict systemic inflammatory response syndrome (SIRS) after endoscopic surgery for kidney stones. The goal is to identify high-risk patients early and provide valuable guidance for urologists i...

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Detalhes bibliográficos

Principais autores:	Jiaxin Li, Yao Du, Gaoming Huang, Yawei Huang, Xiaoqing Xi, Zhenfeng Ye
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Nature Portfolio 2025-02-01
coleção:	Scientific Reports
Assuntos:	Machine learning Renal endoscopic lithotripsy Urosepsis CT values Shapley Additive exPlanations (SHAP)
Acesso em linha:	https://doi.org/10.1038/s41598-025-88704-y
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