About this document
Sensors 25 00824 V2 by varunthej0404 is a document available to read on EtoBox.
This study presents a vision transformer model designed to predict fatal arrhythmic events in patients with Brugada syndrome using 12-lead ECG images. The model was trained on a dataset of 278 ECGs, achieving an accuracy of 89% on a balanced dataset and improved predictions on an unbalanced dataset with 74% accuracy. The research highlights the potential of AI in enhancing risk stratification for asymptomatic patients at risk of sudden cardiac death.
- Author
- varunthej0404
- Language
- EN