MAGNET fuses partial multimodal embeddings via dynamic attention and constructs missingness-aware patient graphs for GNN-based cancer classification, outperforming prior fusion methods on three multiomics datasets.
DrFuse: learning disentangled representation for clinical multi-modal fusion with missing modality and modal inconsistency
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Missing-Modality-Aware Graph Neural Network for Cancer Classification
MAGNET fuses partial multimodal embeddings via dynamic attention and constructs missingness-aware patient graphs for GNN-based cancer classification, outperforming prior fusion methods on three multiomics datasets.