On Icentia11k, self-supervised ECG models trained on 5-10 minute windows with continuous CNN patch embeddings outperform 16-second and vector-quantized models on AFib/AFL detection and patient retrieval.
An artificial intelligence-enabled ecg algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction,
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The Impact of Temporal Context Length and Encoding Strategies on Self-Supervised ECG Representation Learning
On Icentia11k, self-supervised ECG models trained on 5-10 minute windows with continuous CNN patch embeddings outperform 16-second and vector-quantized models on AFib/AFL detection and patient retrieval.