Perineural Invasion (PNI) Classification on PNI R + S (100% Balanced)
0.7903Mean AUCPattenNet
Evaluation results
| Method | Links | |
|---|---|---|
| PattenNetImplementation=3D, Validation=5-fold cross-validation2026.03 | 0.7903 | |
| EfficientNet-B3Implementation=3D, Validation=5-fold cross-validation2026.03 | 0.7755 | |
| ResNet-50Implementation=3D, Validation=5-fold cross-validation2026.03 | 0.7618 | |
| DenseNet-169Implementation=3D, Validation=5-fold cross-validation2026.03 | 0.7584 | |
| DenseNet-121Implementation=3D, Validation=5-fold cross-validation2026.03 | 0.7551 | |
| ResNet-152Implementation=3D, Validation=5-fold cross-validation2026.03 | 0.7526 | |
| SwinTransformerImplementation=3D, Validation=5-fold cross-validation2026.03 | 0.7522 | |
| ResNet-200Implementation=3D, Validation=5-fold cross-validation2026.03 | 0.7412 | |
| DenseNet-201Implementation=3D, Validation=5-fold cross-validation2026.03 | 0.7311 | |
| ResNet-101Implementation=3D, Validation=5-fold cross-validation2026.03 | 0.7203 | |
| EfficientNet-B1Implementation=3D, Validation=5-fold cross-validation2026.03 | 0.7186 | |
| DenseNet-264Implementation=3D, Validation=5-fold cross-validation2026.03 | 0.7155 | |
| EfficientNet-B2Implementation=3D, Validation=5-fold cross-validation2026.03 | 0.711 | |
| EfficientNet-B0Implementation=3D, Validation=5-fold cross-validation2026.03 | 0.6998 |