Table 4.
Sensitivity, specificity, precision, and F1-score comparisons between the baseline VGG16, FP-VGG16, and OSFP-Net. The best results are highlighted in bold. The listed metrics were obtained on the test dataset.
| Fold | Method | Metrics (%) | |||
|---|---|---|---|---|---|
| SEN | SPE | PRE | F1-score | ||
| 1 | VGG16 | 79.5 | 83.0 | 66.0 | 72.1 |
| FP-VGG16 | 87.5 | 100.0 | 100.0 | 93.3 | |
| OSFP-Net | 95.8 | 95.2 | 92.0 | 93.9 | |
| 2 | VGG16 | 74.0 | 85.5 | 75.5 | 74.7 |
| FP-VGG16 | 80.0 | 95.7 | 88.9 | 84.2 | |
| OSFP-Net | 95.0 | 95.7 | 90.5 | 92.7 | |
| 3 | VGG16 | 81.6 | 90.5 | 83.3 | 82.5 |
| FP-VGG16 | 80.0 | 100.0 | 100.0 | 88.9 | |
| OSFP-Net | 90.0 | 100.0 | 100.0 | 94.7 | |
| 4 | VGG16 | 84.7 | 89.2 | 86.2 | 85.5 |
| FP-VGG16 | 95.7 | 90.7 | 84.6 | 89.8 | |
| OSFP-Net | 100.0 | 100.0 | 100.0 | 100.0 | |
| 5 | VGG16 | 88.9 | 91.8 | 80.0 | 84.2 |
| FP-VGG16 | 93.1 | 100.0 | 100.0 | 96.4 | |
| OSFP-Net | 100.0 | 97.3 | 96.7 | 98.3 | |
| Avg. ±Std. | VGG16 | 81.8 ± 5.0 | 88.0 ± 3.3 | 78.2 ± 7.1 | 79.8 ± 5.4 |
| FP-VGG16 | 88.4 ± 6.8 | 97.3 ± 3.7 | 94.7 ± 6.6 | 91.2 ± 4.7 | |
| OSFP-Net | 96.2 ± 3.7 | 97.6 ± 2.0 | 95.8 ± 4.0 | 95.9 ± 2.8 | |