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Explainable Machine Learning Model for Predicting Persistent Sepsis-Associated Acute Kidney Injury: Development and Validation Study

Explainable Machine Learning Model for Predicting Persistent Sepsis-Associated Acute Kidney Injury: Development and Validation Study

The study by Jiang et al [27] used an ML method to build a predictive model, but they did not target patients with sepsis, and the model was not externally validated. In our study, we developed an interpretable ML model in 4 retrospective cohorts and 1 prospective cohort, aimed at early and accurate prediction of persistent sepsis-associated AKI.

Wei Jiang, Yaosheng Zhang, Jiayi Weng, Lin Song, Siqi Liu, Xianghui Li, Shiqi Xu, Keran Shi, Luanluan Li, Chuanqing Zhang, Jing Wang, Quan Yuan, Yongwei Zhang, Jun Shao, Jiangquan Yu, Ruiqiang Zheng

J Med Internet Res 2025;27:e62932

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