Synthetic ECG data from diffusion and VQ-VAE models provides only marginal classification gains on individual datasets, a small boost when datasets are merged, and cannot replace real data in transfer learning.
Commentary: The Problem of Class Imbalance in Biomedical Data,
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Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification
Synthetic ECG data from diffusion and VQ-VAE models provides only marginal classification gains on individual datasets, a small boost when datasets are merged, and cannot replace real data in transfer learning.