Fig. 5
Comparison of bar plots and ROC curves across methods and datasets. (a) Pearson correlation coefficients for different methods across the five datasets, indicating the strength of linear relationships between predicted and true tumor percentages. (b) Spearman correlation coefficients across the five datasets, showcasing the rank-based correlation between predictions and ground truth. (c-e) Receiver Operating Characteristic (ROC) curves for tumor detection with AUC scores for CAM16 (c), ExaMode (d), and COBRA (e), illustrating the trade-off between true positive and false positive rates. The shaded areas represent the confidence intervals over the 5-fold cross-validation, and the mean AUC values with standard deviations are reported for each dataset. These results are based on models trained using true tumor percentages.
