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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 Akoum
Published 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.
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