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Elias Karabelas

Researcher at University of Graz

Publications -  24
Citations -  457

Elias Karabelas is an academic researcher from University of Graz. The author has contributed to research in topics: Finite element method & Computer science. The author has an hindex of 7, co-authored 22 publications receiving 156 citations. Previous affiliations of Elias Karabelas include Graz University of Technology & King's College London.

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Journal ArticleDOI

The openCARP simulation environment for cardiac electrophysiology.

TL;DR: OpenCARP as discussed by the authors is a Python-based simulator for cardiac electrophysiology, which allows developing and sharing simulation pipelines which automate in silico experiments including all modeling and simulation steps to increase reproducibility and productivity.
Journal ArticleDOI

A Framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs.

TL;DR: In this paper, the authors proposed a novel workflow for the generation of high-fidelity CDTs by introducing a comprehensive parameter vector encapsulating all factors relating to the ventricular EP; an abstract reference frame within the model allowing the unattended manipulation of model parameter fields; and a novel fast-forward electrocardiogram (Electrocardiograms) model for efficient and bio-physically-detailed simulation required for parameter inference.
Journal ArticleDOI

Automating image-based mesh generation and manipulation tasks in cardiac modeling workflows using Meshtool.

TL;DR: Meshtool is software specifically designed for automating all complex mesh manipulation tasks emerging in such workflows by implementing algorithms for tasks described as operations on label fields and/or geometric features.
Posted ContentDOI

The openCARP Simulation Environment for Cardiac Electrophysiology

TL;DR: OpenCARP as mentioned in this paper is a Python-based simulator for cardiac electrophysiology, which allows developing and sharing simulation pipelines which automate in silico experiments including all modeling and simulation steps to increase reproducibility and productivity.