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. 2025 May 1;21(5):843–854. doi: 10.5664/jcsm.11560

Figure 2. The distribution and performance of the screening models in the test dataset.

Figure 2

(A) The performance of the screening models built by different machine learning techniques. (B) The kernel density plot of STOP-BANG scores. (C) The kernel density plot of facial photo scores. (D) The kernel density plot of values calculated from the logistic regression model. AUROC = area under the receiver operating characteristic, LR = logistic regression, RF = random forest, SBQ = STOP-BANG questionnaire, SVM = support vector machine, XGBoost = extreme gradient boosting.