Medical Image Classification on MILK Dermoscopic 10k
0.9132AUCMONET
Evaluation results
| Method | Links | ||||||
|---|---|---|---|---|---|---|---|
| MONETType=Concept-based model2026.02 | 0.9132 | 0.5832 | 0.5778 | 73.07 | 74.03 | 1.28 | |
| CLIP2026.02 | 0.9125 | 0.5436 | 0.5556 | 63.92 | 68.76 | 2.19 | |
| ENet-B0Backbone=EfficientNet-B02026.02 | 0.9114 | 0.5763 | 0.5778 | 75.03 | 74.9 | 3.86 | |
| ENet-B0+CBLBackbone=EfficientNet-B0, Loss Function=Class-Balanced Loss2026.02 | 0.9091 | 0.5662 | 0.5556 | 73.92 | 74.04 | 2.03 | |
| SemCovNet2026.02 | 0.9049 | 0.5991 | 0.6222 | 78.74 | 75.73 | 1.74 | |
| ViTModel Type=Vision Transformer2026.02 | 0.9032 | 0.4852 | 0.4 | 67.01 | 68.87 | 4 | |
| GroupDROMethodology=Distributionally Robust Optimization2026.02 | 0.8733 | 0.4913 | 0.4889 | 75.82 | 68.06 | 3.52 | |
| ENet-B0+ASLBackbone=EfficientNet-B0, Loss Function=Asymmetric Loss2026.02 | 0.7201 | 0.267 | 0.2889 | 54.93 | 56.61 | 6.75 |