activity
20172023
most citedInference of ventricular activation properties from non-invasive electrocardiography

54 citations · 72 across the 6 of their papers we have counts for

collaborators

6 papers

physics.med-ph2023★ 2 cited

Digital Twinning of the Human Ventricular Activation Sequence to Clinical 12-lead ECGs and Magnetic Resonance Imaging Using Realistic Purkinje Networks for in Silico Clinical Trials

Julia Camps, Lucas Arantes Berg, Zhinuo Jenny Wang +12

Cardiac in silico clinical trials can virtually assess the safety and efficacy of therapies using human-based modelling and simulation. These technologies can provide mechanistic e…

cs.CV2023

Influence of Myocardial Infarction on QRS Properties: A Simulation Study

Lei Li, Julia Camps, Zhinuo +4

The interplay between structural and electrical changes in the heart after myocardial infarction (MI) plays a key role in the initiation and maintenance of arrhythmia. The anatomic…

cs.CV2022★ 1 cited

Deep Computational Model for the Inference of Ventricular Activation Properties

Lei Li, Julia Camps, Abhirup Banerjee +3

Patient-specific cardiac computational models are essential for the efficient realization of precision medicine and in-silico clinical trials using digital twins. Cardiac digital t…

q-bio.TO2020★ 54 cited

Inference of ventricular activation properties from non-invasive electrocardiography

Julia Camps, Brodie Lawson, Christopher Drovandi +5

The realisation of precision cardiology requires novel techniques for the non-invasive characterisation of individual patients' cardiac function to inform therapeutic and diagnosti…

stat.ML2017★ 1 cited

Variational Inference over Non-differentiable Cardiac Simulators using Bayesian Optimization

Adam McCarthy, Blanca Rodriguez, Ana Minchole

Performing inference over simulators is generally intractable as their runtime means we cannot compute a marginal likelihood. We develop a likelihood-free inference method to infer…

q-bio.TO2017★ 14 cited

Unlocking datasets by calibrating populations of models to data density: a study in atrial electrophysiology

Brodie A. J. Lawson, Christopher C. Drovandi, Nicole Cusimano +3

The understanding of complex physical or biological systems nearly always requires a characterisation of the variability that underpins these processes. In addition, the data used…