AI RESEARCH
Sampling Matters: The Effect of ECG Frequency on Deep Learning-Based Atrial Fibrillation Detection
arXiv CS.LG
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ArXi:2604.16437v1 Announce Type: cross Deep learning models for atrial fibrillation (AF) detection are increasingly trained on heterogeneous electrocardiogram (ECG) datasets with varying sampling frequencies, yet the specific consequences of these discrepancies on model performance, calibration, and robustness remain insufficiently characterized.