Table 5 Performance metrics of the image-level malignancy prediction model with different lesion identification models (one-class, malignancy and sub-types) and aggregation strategies (average, noisy OR and max pooling). The best performing combination is highlighted in boldface.
From: Lesion identification and malignancy prediction from clinical dermatological images
| Â | Average | Noisy OR | Max | |||
|---|---|---|---|---|---|---|
Detection | AUC | AP | AUC | AP | AUC | AP |
Malignancy | 0.7698 | 0.7759 | 0.7698 | 0.7461 | 0.7690 | 0.7772 |
Sub-type | 0.7784 | 0.7822 | 0.7698 | 0.7600 | 0.7643 | 0.7705 |
One-class | 0.7759 | 0.7650 | 0.7783 | 0.7661 | 0.7868 | 0.7821 |
