activity
20172024
most citedUnlocking datasets by calibrating populations of models to data density: a study in atrial electrophysiology

14 citations · 22 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CE20245 cited

Cardiac Digital Twin Pipeline for Virtual Therapy Evaluation

Julia Camps, Zhinuo Jenny Wang, Ruben Doste +6

Cardiac digital twins are computational tools capturing key functional and anatomical characteristics of patient hearts for investigating disease phenotypes and predicting response…

stat.ME20221 cited

Population Calibration using Likelihood-Free Bayesian Inference

Christopher Drovandi, Brodie Lawson, Adrianne L Jenner +1

In this paper we develop a likelihood-free approach for population calibration, which involves finding distributions of model parameters when fed through the model produces a set o…

physics.bio-ph2021

Arrhythmogenicity of cardiac fibrosis: fractal measures and Betti numbers

Mahesh Kumar Mulimani, Brodie A. J. Lawson, Rahul Pandit

Infarction- or ischaemia-induced cardiac fibrosis can be arrythmogenic. We use mathematcal models for diffuse fibrosis (), interstitial fibrosis (), pat…

physics.med-ph20202 cited

Homogenisation for the monodomain model in the presence of microscopic fibrotic structures

Brodie A. J. Lawson, Rodrigo Weber dos Santos, Ian W. Turner +3

Computational models in cardiac electrophysiology are notorious for long runtimes, restricting the numbers of nodes and mesh elements in the numerical discretisations used for thei…

q-bio.TO201714 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…