A waveform-CNN plus spectrogram-transformer plus Bi-GRU fusion reports state-of-the-art sensitivity (90.3%) and total score (93.6%) for binary abnormal versus normal respiratory sound classification on SPRSound.
Artificial intelligence for heart sound classification: A review
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Waveform-Logmel Audio Neural Networks for Respiratory Sound Classification
A waveform-CNN plus spectrogram-transformer plus Bi-GRU fusion reports state-of-the-art sensitivity (90.3%) and total score (93.6%) for binary abnormal versus normal respiratory sound classification on SPRSound.