List your company

Medical Image Classification on AD

79.12AccuracyLoRKD
68.792871.473974.15576.8361Apr 26, 2024

Evaluation results

MethodLinks
LoRKDPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.0479.12
LoRKDPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.0479.05
MoCo-MTLPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.0477.8
Aligned-MTLPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.0477.72
MTLPre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.0477.48
MoCo-MTLPre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.0477.48
MTLPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.0477.17
LoRKDPre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.0476.94
STLPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.0476.7
MTL-KDPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.0476.62
Aligned-MTLPre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.0476.62
STL-KDPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.0476.31
BaselinePre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.0476.08
BaselinePre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.0476.08
BaselinePre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.0476.08
KFPre-train=Med-MT, Params(M)=1.60, Comp. Ratio=6.81%2024.0475.76
MTLPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.0474.67
MTL-KDPre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.0474.43
FoundationPre-train=Radimagenet, Params(M)=23.51, Comp. Ratio=/2024.0474.35
MTL-KDPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.0473.89
KFPre-train=MedMnist, Params(M)=1.60, Comp. Ratio=6.81%2024.0472.71
FoundationPre-train=MedMnist, Params(M)=23.51, Comp. Ratio=/2024.0472.09
KFPre-train=Radimagenet, Params(M)=1.60, Comp. Ratio=6.81%2024.0471.23
Aligned-MTLPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.0470.29
MoCo-MTLPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.0469.27
FoundationPre-train=Med-MT, Params(M)=23.51, Comp. Ratio=/2024.0469.19