Nicholas S. Peters
www.imperial.ac.uk
0000-0002-3581-8078
6 papers found
Refreshing results…
Machine learning-derived cycle length variability metrics predict spontaneously terminating ventricular tachycardia in implantable cardioverter defibrillator recipients
Should lethal arrhythmias in hypertrophic cardiomyopathy be predicted using non-electrophysiological methods?
Ablation versus anti-arrhythmic therapy for reducing all hospital episodes from recurrent atrial fibrillation: a prospective, randomized, multi-centre, open label trial
Prognostic Significance of Ventricular Arrhythmias in 13 444 Patients With Acute Coronary Syndrome: A Retrospective Cohort Study Based on Routine Clinical Data (NIHR Health Informatics Collaborative VA‐ACS Study)
RETRO-MAPPING: A New Approach to Activation Mapping in Persistent Atrial Fibrillation Reveals Evidence of Spatiotemporal Stability
Artificial Intelligence and Machine Learning in Arrhythmias and Cardiac Electrophysiology
Missing publications? Search for publications with a matching author name.