3 papers
eess.IV2026
Towards Deep Learning Surrogate for the Forward Problem in Electrocardiology: A Scalable Alternative to Physics-Based Models
Shaheim Ogbomo-Harmitt, Cesare Magnetti, Chiara Spota +2
The forward problem in electrocardiology, computing body surface potentials from cardiac electrical activity, is traditionally solved using physics-based models such as the bidomai…
cs.LG2026
Dynamical Predictive Modelling of Cardiovascular Disease Progression Post-Myocardial Infarction via ECG-Trained Artificial Intelligence Model
Riccardo Cavarra, Lupo Lovatelli, Shaheim Ogbomo-Harmitt +4
Myocardial infarction (MI) is a leading cause of death, and its adverse outcomes are urgent to predict. Yet ECG-based prognostic models underperform because deep learning requires…
cs.CV2026
Neural Surrogate Forward Modelling For Electrocardiology Without Explicit Intracellular Conductivity Tensor
Shaheim Ogbomo-Harmitt, Cesare Magnetti, Jakub Grzelak +1
Accurate forward modelling is essential for non-invasive cardiac electrophysiology, particularly in atrial fibrillation, where electrical activation is highly disorganised. Convent…