AuthorsM. Vagos, H. Arevalo, F. Sacco and M. Maleckar
TitleA data-driven framework uncovers arrhythmogenic mechanisms in a 'functionally calibrated' population of models
AfilliationScientific Computing
Project(s)AFib-TrainNet: EU Training Network on Novel Targets and Methods in Atrial Fibrillation, Center for Biomedical Computing (SFF)
Publication TypePoster
Year of Publication2017
Place PublishedBiophysical Society 61st Annual Meeting, New Orleans, Louisiana, USA

Human atrial cell models have been used to establish electrophysiological properties in normal sinus rhythm (nSR) or in atrial fibrillation (AF). However, the complexity of these models makes elucidation of the mechanisms underlying arrhythmigenic behavior difficult. This study presents a data-driven methodology that can be used to identify novel arrhythmogenic mechanisms in a 'functionally calibrated' populations of models.

Citation Key25393