HiLa aligns multiple survival-related language prompts with patch- and region-level slide features using optimal transport, contrastive learning, and cross-level gating, achieving higher C-index on three TCGA cohorts.
and Ji, X .: Transmil: Transformer based correlated multiple instance learning for whole slide image classification
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
HiLa: Hierarchical Vision-Language Collaboration for Cancer Survival Prediction
HiLa aligns multiple survival-related language prompts with patch- and region-level slide features using optimal transport, contrastive learning, and cross-level gating, achieving higher C-index on three TCGA cohorts.