From: Deep learning and radiomics framework for PSMA-RADS classification of prostate cancer on PSMA PET
Inputs | AUROC | Accuracy | Precision | Recall | F1 score |
---|---|---|---|---|---|
Validation set: Lesion-level performance | |||||
 Manual | 0.98 (0.98, 0.98) | 0.94 (0.92, 0.95) | 0.95 | 0.94 | 0.94 |
 Predicted RF | 0.98 (0.98, 0.98) | 0.93 (0.91, 0.95) | 0.94 | 0.93 | 0.94 |
 Predicted TT | 0.95 (0.95, 0.95) | 0.89 (0.87, 0.91) | 0.91 | 0.89 | 0.90 |
 Predicted RF + TT | 0.95 (0.95, 0.95) | 0.89 (0.86, 0.91) | 0.91 | 0.88 | 0.90 |
Test set: Lesion-level performance | |||||
 Manual | 0.96 (0.96, 0.96) | 0.89 (0.87, 0.92) | 0.81 | 0.94 | 0.87 |
 Predicted RF | 0.96 (0.96, 0.96) | 0.89 (0.87, 0.91) | 0.80 | 0.93 | 0.86 |
 Predicted TT | 0.92 (0.92, 0.92) | 0.85 (0.83, 0.88) | 0.79 | 0.81 | 0.80 |
 Predicted RF + TT | 0.92 (0.92, 0.92) | 0.85 (0.82, 0.87) | 0.79 | 0.80 | 0.80 |
Test set: Patient-level performance | |||||
 Manual | 0.84 (0.84, 0.85) | 0.92 (0.85, 1.00) | 0.93 | 0.98 | 0.96 |
 Predicted RF | 0.88 (0.87, 0.88) | 0.92 (0.85, 1.00) | 0.93 | 0.98 | 0.96 |
 Predicted TT | 0.84 (0.84, 0.85) | 0.89 (0.80, 0.97) | 0.93 | 0.93 | 0.93 |
 Predicted RF + TT | 0.85 (0.84, 0.86) | 0.89 (0.80, 0.97) | 0.93 | 0.93 | 0.93 |