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A single foundation model can effectively leverage heterogeneous cardiac signals to achieve superior performance across multiple tasks, defying the limitations of modality-specific training.
Unlock vast troves of legacy ECG image data for automated cardiovascular diagnostics with a self-supervised framework that rivals signal-based analysis.
