Electrocardiogram-based deep learning improves outcome prediction following cardiac resynchronization therapy.

Aims: This study aims to identify and visualize electrocardiogram (ECG) features using an explainable deep learning-based algorithm to predict cardiac resynchronization therapy (CRT) outcome. Its performance is compared with current guideline ECG criteria and QRSAREA.

Methods And Results: A deep learning algorithm, trained on 1.