2 citations · 2 across the 3 of their papers we have counts for
4 papers
LogitDynamics: Reliable ViT Error Detection from Layerwise Logit Trajectories
Ido Beigelman, Moti Freiman
Reliable confidence estimation is critical when deploying vision models. We study error prediction: determining whether an image classifier's output is correct using only signals f…
PSA-MIL: A Probabilistic Spatial Attention-Based Multiple Instance Learning for Whole Slide Image Classification
Sharon Peled, Yosef E. Maruvka, Moti Freiman
Whole Slide Images (WSIs) are high-resolution digital scans widely used in medical diagnostics. WSI classification is typically approached using Multiple Instance Learning (MIL), w…
Multi-Cohort Framework with Cohort-Aware Attention and Adversarial Mutual-Information Minimization for Whole Slide Image Classification
Sharon Peled, Yosef E. Maruvka, Moti Freiman
Whole Slide Images (WSIs) are critical for various clinical applications, including histopathological analysis. However, current deep learning approaches in this field predominantl…
CIMIL-CRC: a clinically-informed multiple instance learning framework for patient-level colorectal cancer molecular subtypes classification from H\&E stained images
Hadar Hezi, Matan Gelber, Alexander Balabanov +2
Treatment approaches for colorectal cancer (CRC) are highly dependent on the molecular subtype, as immunotherapy has shown efficacy in cases with microsatellite instability (MSI) b…