Abstract
In this paper, we propose to use convolutional neural networks for automatic wheeze detection in lung sounds. We present convolutional neural network based approach that has several advantages compared to the previous approaches described in the literature. Our method surpasses the standard machine learning models on this task. It is robust to lung sound shifting and requires minimal feature preprocessing steps. Our approach achieves 99% accuracy and 0.96 AUC on our datasets.
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Kochetov, K., Putin, E., Azizov, S., Skorobogatov, I., Filchenkov, A. (2017). Wheeze Detection Using Convolutional Neural Networks. In: Oliveira, E., Gama, J., Vale, Z., Lopes Cardoso, H. (eds) Progress in Artificial Intelligence. EPIA 2017. Lecture Notes in Computer Science(), vol 10423. Springer, Cham. https://doi.org/10.1007/978-3-319-65340-2_14
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DOI: https://doi.org/10.1007/978-3-319-65340-2_14
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