Bridging the gap between subjective and objective measures: A multimodal protocol for adolescent depression detection

Figure 1 Performance comparison. A: Multimodal performance comparison; B: Bimodal performance comparison. XGBoost: Extreme gradient boosting; AUC-ROC: Under the receiver operating characteristic curve; AUC-PR: Area under the precision-recall curve.

Figure 2 Coefficient of variation comparison across performance metrics. AUC-ROC: Under the receiver operating characteristic curve; AUC-PR: Area under the precision-recall curve.

Figure 3 Learning curves of training and validation accuracy. A: Multimodal extreme gradient boosting models; B: Bimodal extreme gradient boosting models.

Figure 4 Confusion matrices. A: Confusion matrices for multimodal extreme gradient boosting models; B: Bimodal extreme gradient boosting models.