REVEAL uses vision-language alignment of retinal morphometry and clinical risk narratives plus group contrastive learning to predict AD and dementia about 8 years early.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
REVEAL++ replaces discrete phenotypic groups with differentiable soft multi-positive weighting derived from intra-modality embeddings in contrastive learning, outperforming prior discrete and baseline methods on UK Biobank incident AD prediction.
citing papers explorer
-
REVEAL++: Differentiable Phenotypic Grouping for Vision-Language Retinal Modeling of Alzheimer's Disease Risk
REVEAL++ replaces discrete phenotypic groups with differentiable soft multi-positive weighting derived from intra-modality embeddings in contrastive learning, outperforming prior discrete and baseline methods on UK Biobank incident AD prediction.