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. 2025 Aug 8;15:1623109. doi: 10.3389/fcimb.2025.1623109

Figure 4.

ROC curve comparing different models: Bayes, Decision Tree, Logistic Regression, MLP, Random Forest, SVM, and XGBoost. Curves show varying sensitivity and specificity. XGBoost and Random Forest exhibit highest AUC values around 0.904 and 0.906 respectively.

Comparison of ROC curves of seven models in the training cohort. Red line =Bayes model, orange line = DT model, green line = LR model, blue line = MLP model, dark purple line = RF model, bright purple line = SVM model, yellow line = XGBoost model.