Emulation of cardiac mechanics using graph neural networks

DOI10.1016/j.cma.2022.115645OpenAlexW4302425293MaRDI QIDQ2096869

Hao Gao, Dirk Husmeier, David R. Dalton

Publication date: 11 November 2022

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cma.2022.115645

zbMATH Keywords

cardiac mechanicsemulationgraph neural networks

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Artificial neural networks and deep learning (68T07) Biomechanics (92C10)

Related Items (2)

Physics-informed graph neural network emulation of soft-tissue mechanics ⋮ Emulation of cardiac mechanics using graph neural networks

Uses Software

• Scikit
• Adam
• GitHub
• JAX
• Flax

Cites Work

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• State space reconstruction in the presence of noise
• Physics-informed graph neural Galerkin networks: a unified framework for solving PDE-governed forward and inverse problems
• Emulation of cardiac mechanics using graph neural networks
• Simulation of the 3D hyperelastic behavior of ventricular myocardium using a finite-element based neural-network approach
• A comparison of neural network architectures for data-driven reduced-order modeling
• Integrated heart -- coupling multiscale and multiphysics models for the simulation of the cardiac function
• Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
• Bayesian Calibration of Computer Models
• Solving PDEs in Python
• Constitutive modelling of passive myocardium: a structurally based framework for material characterization
• Physical Systems with Random Uncertainties: Chaos Representations with Arbitrary Probability Measure

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