Key Findings:
• Artificial Intelligence and machine learning have significantly impacted the field of cardiac electrophysiology.
• Application of AI to EKG, data from wearables and smart devices can provide information beyond human capabilities for risk stratification, disease screening, and detection of noncardiac conditions.
• AI can potentially be used to streamline workflow around remote monitoring of implantable cardiac devices, predict ICD therapies and response to CRT.
• AI can be used to identify sites of successful ablation and predict response to ablative therapies.
• Personalized computation modelling provides an individualized non-invasive approach to determine targets of ablation in ventricular tachycardia and persistent AF and determine arrhythmia risk in patients with heart disease