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Interpretable machine learning for chronic kidney disease prediction: Insights from SHAP and LIME analyses

Fig 3

ROC curve comparison for Dataset 1 (UAE Tawam Hospital).

Panel A: without SMOTE; Panel B: with SMOTE. XGBoost demonstrates improved discrimination with SMOTE (AUC: 0.886 → 0.904).

Fig 3

doi: https://doi.org/10.1371/journal.pone.0343205.g003