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Multiple Instance Learning On Tcga

Métriques

ACC

AUC

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	ACC	AUC	Paper Title	Repository
Snuffy (SimCLR Exhaustive)	0.947	0.972	Snuffy: Efficient Whole Slide Image Classifier	-
DTFD-MIL (MaxS)	0.868	0.919	DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification	-
DTFD-MIL (MaxMinS)	0.891	0.961	DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification	-
DTFD-MIL (MAS)	-	0.955	DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification	-
TransMIL	0.8835	0.9603	TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification	-
DSMIL-LC	0.9286	0.9583	Dual-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	-
DSMIL	0.9190	0.9633	Dual-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