The Beat Webinar Series Episode 19:From Concepts to Clinic: the 5 Most Gaming-Changing AbstracX at HRX 2025, Recorded LIVE at HRX 2025 in Atlanta (On-Demand)-The 5 Most Game-Changing AbstracX at HRX 2025

Video Transcription

Video Summary

This episode of The Beat webinar, recorded at the innovative HRX meeting, highlights five cutting-edge electrophysiology (EP) abstracts, with expert commentary from Drs. Jonathan Piccini and Suneet Mittal. The first abstract introduces Empower AI, an app leveraging large language models to improve clinical billing accuracy by analyzing physician notes, addressing significant billing losses. Discussion emphasized practical clinical utility amid coding complexity and the potential integration of AI in EHR systems, though human oversight remains vital. The second abstract presents AI using ResNet neural networks to predict undiagnosed atrial fibrillation (AF) from 12-lead ECGs in stroke patients, showing promise but with moderate accuracy, highlighting challenges near clinical action thresholds. Third, a real-time patient-specific digital twin of the left atrium simulates arrhythmias and ablation effects, offering personalized procedural guidance and potential as a training tool, enabled by advances in imaging and computing speed. Fourth, a novel resizable soft robotic catheter made from conformable polymers enables rapid whole-chamber mapping with integrated ablation, representing a breakthrough in material science and EP device design. Finally, a variable e-textile system for long-term AF burden monitoring offers an electrogram-based, comfortable wearable alternative to traditional monitors and consumer PPG devices, with clinician portals enhancing clinical decision-making. These innovations underscore the vibrant collaboration between clinicians and industry, pointing to a future of personalized, efficient, and data-driven arrhythmia management.

Keywords

Electrophysiology

AI in Clinical Billing

Atrial Fibrillation Prediction

Digital Twin Simulation

Soft Robotic Catheter

E-textile Wearable Monitoring

Personalized Arrhythmia Management