Use of Wearable Technology and Deep Learning to Improve the Diagnosis of Brugada Syndrome

This novel DL model achieved cardiologist-level accuracy in classifying Brugada type 1. Applying DL to 24-hour 12-lead Holters significantly improved the detection of Brugada type 1 in patients with procainamide-induced and suspected Brugada syndrome. DL analysis of 12-lead Holters may provide a robust, automated screening tool before procainamide challenge to aid in the diagnosis of Brugada syndrome.