QECGBERT tokenizes ECG waveforms for BERT-style pretraining
It is pretrained on more than 800,000 unlabeled MIMIC-IV ECGs and fine-tuned on three labeled datasets.
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It is pretrained on more than 800,000 unlabeled MIMIC-IV ECGs and fine-tuned on three labeled datasets.
Next-Concept Modeling generates text coarse-to-fine in parallel, up to 31 times faster than diffusion language models.
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