Does a deep learning system analyzing PPG waveforms improve the detection of atrial fibrillation compared to handcrafted feature methods in adults screened in primary care?
A deep learning system analyzing PPG waveforms effectively detects atrial fibrillation in primary care settings, outperforming traditional feature-based methods.
In this evaluation of PPG waveforms from adults screened for AF in a real-world primary care setting, the DCNN had high sensitivity, specificity, PPV and NPV for detecting AF, outperforming other state-of-the-art methods based on handcrafted features.
Poh et al. (Thu,) studied this question.
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