Kun Li

Robust multi-label ECG classification: a deep learning framework for concurrent arrhythmias with clinical generalizability

This study proposes a cascaded deep learning model based on a residual structure, named ResCGT-Net, for multi-label one-dimensional ECG signal recognition and classification, offering an efficient and reliable solution for automated multi-label arrhythmia analysis, with significant clinical application value.