Medicine XAI May - August 2022

1. The article states that recognizing lung sound patterns is critical to detecting and monitoring respiratory disease. Current techniques for breath sound analysis used by industry experts are subject to interpretation. Therefore, a precise and automatic breath sound classification system is desirable. In this work, we took a data-driven approach to classify abnormal lung sounds. The authors compared the performance with three different functions extraction techniques, which are Short Time Fourier Transform (STFT), Mel and Wav2vec spectrograms, as well as three different classifiers including pre-trained ResNet18, LightCNN, and audio spectrogram transformer. The authors' fundamental contribution contains a comparative analysis of different audio feature extractors and classifiers based on neural networks and their implementation of a complete pipeline with STFT and matched ResNet18 Network. The method proposed has achieved Harmonic Scores at the levels of 0.89, 0.80, 0.71, 0.36 fo...