DeScoD-ECG is a novel deep score-based diffusion model for removing baseline wander and noise from ECGs.
Offers improved ECG signal cleaning for research; leaves open clinical validation before practice change.
This study is one of the first to extend the conditional diffusion-based generative model for ECG noise removal, and the DeScoD-ECG has the potential to be widely used in biomedical applications.
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Li et al. (2023) studied this question.
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