Cough Dataset

Cough datasets are collections of audio recordings used to develop and evaluate artificial intelligence models for diagnosing respiratory diseases. Current research focuses on improving model accuracy and robustness using various deep learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs like LSTMs), and vision transformers, often incorporating techniques like self-supervised learning and federated learning to address data scarcity and privacy concerns. These efforts aim to create reliable, bias-free diagnostic tools that can assist in the early detection and classification of respiratory illnesses, potentially improving healthcare efficiency and patient outcomes. Addressing challenges like data labeling inconsistencies and confounding variables remains a key focus.