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A cross-modal self-attention fusion approach integrating gene expression, copy number alterations, and mutation data provides a scalable and effective alternative to traditional fusion methods for breast cancer subtype classification. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

Cross-Modal Self-Attention Fusion for Breast Cancer Subtype Classification Using Multi-Omics Data

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