Cough Audio

Cough audio analysis uses machine learning, particularly deep learning models like convolutional neural networks (CNNs), recurrent neural networks (RNNs, including LSTMs), and vision transformers, to automatically detect and classify respiratory diseases based on acoustic features. Research focuses on improving model accuracy and robustness, addressing issues like data imbalance and confounding variables through techniques such as semi-supervised learning and bias mitigation strategies. This non-invasive, cost-effective approach holds significant potential for improving disease diagnosis, particularly in resource-limited settings, by aiding in triage and optimizing the use of more expensive diagnostic tools like chest X-rays.