Heart Sound

Heart sound analysis, or phonocardiography (PCG), focuses on automatically identifying and classifying heart sounds to aid in the diagnosis of cardiovascular diseases. Current research emphasizes developing robust machine learning models, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), often incorporating techniques like multi-task learning and transfer learning from large general-purpose audio datasets, to improve accuracy and efficiency in detecting abnormalities such as murmurs and arrhythmias. These advancements aim to improve the speed and accuracy of diagnosis, potentially reducing the reliance on subjective clinical interpretation and improving patient care, especially in resource-limited settings. The development of large, high-quality datasets with diverse pathologies and noise conditions is crucial for further progress in this field.