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icbhi17

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Automated respiratory sound classification using ML and deep learning on the ICBHI 2017 dataset. Patient-aware evaluation with SVM, CNN, CRNN, and ResNet18 across cycle-level (4-class + binary) and patient-level disease diagnosis.

  • Updated Apr 9, 2026
  • Jupyter Notebook

Respiratory sound classification on ICBHI 2017 — comparing PANNs+BiGRU, EfficientNet-B0, and Audio Spectrogram Transformer (AST) with best ICBHI score of 0.6835

  • Updated Jul 6, 2026
  • Jupyter Notebook

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