Medical Image Classification on ChestX-ray14
0.8274Mean AUROCREGSL
Evaluation Results
| Method | Links | |
|---|---|---|
| REGSLBackbone=ResNet-182021.11 | 0.8274 | |
| l2-PGMBackbone=ResNet-182021.11 | 0.8235 | |
| l2-SPBackbone=ResNet-182021.11 | 0.8231 | |
| l2-NormBackbone=ResNet-182021.11 | 0.8198 | |
| SupervisedPretraining Dataset=ImageNet, Backbone=ResNet-50, Evaluation Protocol=Fine-tuning2022.04 | 0.817 | |
| Fine-tuningBackbone=ResNet-182021.11 | 0.8159 | |
| DiRAMoCo-v2Pretraining Dataset=ChestX-ray14, Backbone=ResNet-50, Evaluation Protocol=Fine-tuning2022.04 | 0.8112 | |
| DiRABarlow TwinsPretraining Dataset=ChestX-ray14, Backbone=ResNet-50, Evaluation Protocol=Fine-tuning2022.04 | 0.8088 | |
| DiRAsimSiamPretraining Dataset=ChestX-ray14, Backbone=ResNet-50, Evaluation Protocol=Fine-tuning2022.04 | 0.8044 | |
| RandomPretraining Dataset=None, Backbone=ResNet-50, Evaluation Protocol=Fine-tuning2022.04 | 0.8031 | |
| LSBackbone=ResNet-182021.11 | 0.7885 | |
| NOVA ViT-BFramework=NOVA, Model=ViT-B, # Parameters=92.1M, # Samples Seen=130K, Zero-Shot=true2026.01 | 0.7317 | |
| NOVA ViT-SFramework=NOVA, Model=ViT-S, # Parameters=27.1M, # Samples Seen=130K, Zero-Shot=true2026.01 | 0.7304 | |
| MedCLIP ViT-SFramework=MedCLIP, Model=ViT-S, # Parameters=21.7M, # Samples Seen=130K, Zero-Shot=true2026.01 | 0.6795 | |
| MedCLIP ViT-BFramework=MedCLIP, Model=ViT-B, # Parameters=86.0M, # Samples Seen=130K, Zero-Shot=true2026.01 | 0.667 | |
| CLIP (SigLIP) ViT-BFramework=CLIP, Algorithm=SigLIP, Model=ViT-B, # Parameters=150.0M, # Samples Seen=1.41M, Zero-Shot=true2026.01 | 0.6639 | |
| CLIP (InfoNCE) ViT-BFramework=CLIP, Algorithm=InfoNCE, Model=ViT-B, # Parameters=150.0M, # Samples Seen=1.41M, Zero-Shot=true2026.01 | 0.6553 | |
| CLIP (Base) ViT-BFramework=CLIP, Algorithm=Base, Model=ViT-B, # Parameters=150.0M, # Samples Seen=1.28M, Zero-Shot=true2026.01 | 0.5063 |