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The document presents CG-DMER, a contrastive-generative framework designed for disentangled multimodal ECG representation learning, addressing intra-modality and inter-modality issues in existing approaches. It utilizes spatial-temporal masked modeling and representation disentanglement to enhance feature discrimination and mitigate modality-specific biases. Experiments demonstrate CG-DMER

Author

mn9142001

Language

EN