Machine Learning in Atrial Fibrillation

This study is using machine learning (AI-driven analysis) to study electrical patterns of atrial fibrillation (an irregular heart rhythm) during ablation procedures. Researchers are collecting electrical data from the heart to develop better AI models that can predict which ablation strategies will be most effective for individual patients. **You may be eligible if...** - You are undergoing ablation (a procedure to correct heart rhythm) at Stanford for paroxysmal atrial fibrillation (AF that stops on its own in under 7 days) or persistent AF (requires a procedure to stop it) - You have tried or cannot tolerate at least one anti-arrhythmic drug **You may NOT be eligible if...** - You have active coronary ischemia (blocked heart arteries causing symptoms) or severe heart failure - You have a blood clot in your heart - You are pregnant - You are unwilling or unable to give informed consent - You have rheumatic valve disease - You have blood clotting problems or vein filters Talk to your doctor to see if this trial is right for you.