LGNov 1, 2024
Hierarchical Transformer for Electrocardiogram DiagnosisXiaoya Tang, Jake Berquist, Benjamin A. Steinberg et al.
We propose a hierarchical Transformer for ECG analysis that combines depth-wise convolutions, multi-scale feature aggregation via a CLS token, and an attention-gated module to learn inter-lead relationships and enhance interpretability. The model is lightweight, flexible, and eliminates the need for complex attention or downsampling strategies.