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Multiple Instance Learning On Tcga

Metrics

ACC
AUC

Results

Performance results of various models on this benchmark

Model Name
ACC
AUC
Paper TitleRepository
Snuffy (SimCLR Exhaustive)0.9470.972Snuffy: Efficient Whole Slide Image Classifier-
DTFD-MIL (MaxS)0.8680.919DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification-
DTFD-MIL (MaxMinS)0.8910.961DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification-
DTFD-MIL (MAS)-0.955DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification-
TransMIL0.88350.9603TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification-
DSMIL-LC0.92860.9583Dual-stream Multiple Instance Learning Network for Whole Slide Image Classification with Self-supervised Contrastive Learning-
DTFD-MIL (AFS)0.951-DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification-
DSMIL0.91900.9633Dual-stream Multiple Instance Learning Network for Whole Slide Image Classification with Self-supervised Contrastive Learning-
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Multiple Instance Learning On Tcga | SOTA | HyperAI