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    Development and validation of interpretable machine learning models for predicting AKI risk in patients treated with PD-1/PD-L1: a retrospective study by Wentong Liu, Kaiyue Ji, Qianwen Tang, Weiqi Xia, Wei Zhang, Lina Shao, Jiana Shi, Yukun Li, Ping Huang, Xiaolan Ye

    Published 2025-08-01
    “…Additionally, a web-based calculator based on the model was developed. Results Among the nine ML models evaluated, the Grandient Boosting Machine (GBM) model achieved the best predictive performance. …”
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    A Comprehensive Ensemble Model for Marine Atmospheric Boundary-Layer Prediction in Meteorologically Sparse and Complex Regions: A Case Study in the South China Sea by Yehui Chen, Tao Luo, Gang Sun, Wenyue Zhu, Qing Liu, Ying Liu, Xiaomei Jin, Ningquan Weng

    Published 2025-06-01
    “…The SOEM outperformed random forest, extreme gradient boosting, and histogram-based gradient boosting models, achieving a robustness coefficient (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula>) of 0.95 and the lowest mean absolute error of 32 m under the clear/slightly cloudy condition. …”
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