Area of research
Cardiology and Cardiovascular Medicine
Research interest
Research focused on Artificial intelligence and Checklist, with related work in Hypoplastic left heart syndrome, Great arteries, Ablation. Notable publications include 'How to use digital devices to detect and manage arrhythmias: an EHRA practical guide', 'Age is the main determinant of COVID-19 related in-hospital mortality with minimal impact of pre-existing comorbidities, a retrospective cohort study', and 'State of the Art of Artificial Intelligence in Clinical Electrophysiology in 2025: A Scientific Statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart...'.
State of the Art of Artificial Intelligence in Clinical Electrophysiology in 2025: A Scientific Statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart Rhythm Society (HRS), and the ESC Working Group on E-Cardiology
Machine learning of electrophysiological signals for the prediction of ventricular arrhythmias: systematic review and examination of heterogeneity between studies
Predicting success of atrial fibrillation ablation: comparing machine learning approaches of intracardiac electrograms
How to use digital devices to detect and manage arrhythmias: an EHRA practical guide
Age is the main determinant of COVID-19 related in-hospital mortality with minimal impact of pre-existing comorbidities, a retrospective cohort study
Electrocardiogram-based mortality prediction in patients with COVID-19 using machine learning
Automatic left atrial segmentation from cardiac CT using computer graphics imaging and deep learning
Artificial intelligence to reduce artifact in cardiac electrophysiological signals
Clinical phenotyping of implantable cardioverter defibrillator patients to identify the association of remote device monitoring on survival benefit: a cluster analysis
Novel electrogram featurization reveals a spectrum of response to ablation from atrial tachycardia to types of atrial fibrillation
Spatiotemporal signatures of response to atrial fibrillation ablation
Reduction of artifacts and noise in small electrogram datasets without manual annotation using transfer machine learning
Abstract 11648: ECG-Derived Features Enable Prediction of Sudden Death in Ischemic Cardiomyopathy
Abstract 11651: Machine Learning of Action Potential Shape to Define Refractory Periods in Ischemiccardiomyopathy
Abstract 14115: Multivariate Predictors of Long-Term Outcome From Ventricular Tachycardia Ablation in a Large Registry
Abstract 15312: Automatic Left Atrial Volume and Sphericity Index Calculation From Cardiac CT Using Computer Graphics Imaging and Deep Learning
Abstract 15172: Improving Cardiac Segmentation for Atrial Fibrillation Ablation: A Prospective Trial of Machine Learned Geometric Dissection vs Experts
Sequential Defects in Cardiac Lineage Commitment and Maturation Cause Hypoplastic Left Heart Syndrome
Common Genetic Variants Contribute to Risk of Transposition of the Great Arteries