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Compared with the non-AKI group, the AKI group showed a remarkably lower survival rate (P 0.001). The random forest model demonstrated the highest prediction accuracy of 0.79 with AUC of 0.850 [95% confidence interval (CI) 0.794-0.905], which was significantly higher than the AUCs of the other machine learning algorithms and logistic regression models (P 0.001). The random forest model based on machine learning algorithms for predicting AKI occurring after DCDLT demonstrated stronger predictive power than other models in our study. This suggests t
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