Multimodal prognosis models often generalize worse than unimodal ones across cancer types; a sparse rebalancer plus distribution-entanglement module improves cross-cancer C-index from 0.5489 to 0.5625, though hyperparameters were tuned on target data.
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Single Domain Generalization for Multimodal Cross-Cancer Prognosis via Dirac Rebalancer and Distribution Entanglement
Multimodal prognosis models often generalize worse than unimodal ones across cancer types; a sparse rebalancer plus distribution-entanglement module improves cross-cancer C-index from 0.5489 to 0.5625, though hyperparameters were tuned on target data.