Machine learning identifies esophageal luminal temperature patterns associated with thermal injury in catheter ablation for atrial fibrillation.
Yaacoub ChahineTanzina AfrozeSavannah F BifulcoDemyan V TekmenzhiMahbod JafarvandPatrick M BoyleNazem AkoumPublished in: Journal of cardiovascular electrophysiology (2024)
The rate of LET change and AUC for the recorded temperature predicted EDEL, whereas absolute peak temperatures did not.