Atrial constitutive neural networks

Mathias Peirlinck, Kevin Linka, Ellen Kuhl
4/3/2025
cs.CEcond-mat.softcs.LG

No confident code implementation found for this paper.

Abstract

This work presents a novel approach for characterizing the mechanical behavior of atrial tissue using constitutive neural networks. Based on experimental biaxial tensile test data of healthy human atria, we automatically discover the most appropriate constitutive material model, thereby overcoming the limitations of traditional, pre-defined models. This approach offers a new perspective on modeling atrial mechanics and is a significant step towards improved simulation and prediction of cardiac health.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Identifying Constitutive Parameters for Complex Hyperelastic Materials using Physics-Informed Neural Networks

82% match1 repo102023

Physics-informed neural network estimation of active material properties in time-dependent cardiac biomechanical models

82% match2025

From Motion to Meaning: Biomechanics-Informed Neural Network for Explainable Cardiovascular Disease Identification

81% match2025

Viscoelastic Constitutive Artificial Neural Networks (vCANNs) $-$ a framework for data-driven anisotropic nonlinear finite viscoelasticity

81% match1 repo62023

Exploring hyperelastic material model discovery for human brain cortex: multivariate analysis vs. artificial neural network approaches

81% match2023

Generalized invariants meet constitutive neural networks: A novel framework for hyperelastic materials

81% match2025

Cite this paper

@article{peirlinck2025atrial,
  title  = {Atrial constitutive neural networks},
  author = {Mathias Peirlinck and Kevin Linka and Ellen Kuhl},
  year   = {2025},
  eprint = {2504.02748},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2504.02748v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2504.02748.svg)](https://codeofpaper.com/paper/2504.02748)

Discussion