Pathological Image Classification on PAIP 2019 benchmark leaderboard · SOTA2 Research

Pathological Image Classification on PAIP 2019

99.53AccuracySSMamba

Evaluation Results

Method	Links
SSMamba2026.04		99.53
Virchow22026.04		96.53
UNI22026.04		95.65
UNI2026.04		95.6
GigaPath2026.04		94.21
MUSK2026.04		93.05
Swin2026.04		92.1
ViT2026.04		91.89
CTransPath2026.04		89.73
VMamba2026.04		81.67
MAE2026.04		78.2
CONCH2026.04		76.85