ECGXtract: Deep Learning-based ECG Feature Extraction for Automated CVD Diagnosis

ECGXtract is a groundbreaking deep learning approach designed to enhance ECG feature extraction for automated cardiovascular disease diagnosis. This innovative method overcomes the limitations of traditional signal processing and opaque machine learning techniques by utilizing convolutional neural networks to extract both temporal and morphological features that align closely with clinically validated standards. This advancement is significant as it promises to improve diagnostic accuracy and efficiency in healthcare, ultimately leading to better patient outcomes.