AnyECG, a two-stage self-supervised ECG foundation model with a vector-quantized rhythm codebook and sparse attention, reports state-of-the-art numbers on four cardiac tasks, but its evaluation is weakened by in-domain testing and missing data.
Deep learning for ecg arrhythmia detection and classification: an overview of progress for period 2017–2023,
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AnyECG: Foundational Models for Multitask Cardiac Analysis in Real-World Settings
AnyECG, a two-stage self-supervised ECG foundation model with a vector-quantized rhythm codebook and sparse attention, reports state-of-the-art numbers on four cardiac tasks, but its evaluation is weakened by in-domain testing and missing data.