AI-detected ECG signature reveals new high-risk group for sudden cardiac death

A Swedish deep-learning model trained on hundreds of thousands of ECGs linked to death data identifies a 2.2% high-risk group with a 7.0% annual Sudden Cardiac Death rate, most of whom would not be flagged by reduced left ventricular ejection fraction (LVEF); external validation in the US and Taiwan shows the model generalizes to predict arrhythmic events; a generative model visualizes a concrete ECG biomarker and implicates conduction changes related to fibrosis; these findings point to a sizable, previously unrecognized population that could potentially benefit from defibrillators and warrant randomized trials.