ArticleJournal of the Royal Society, Interface2021
Predictive constitutive modelling of arteries by deep learning.
Article in Journal of the Royal Society, Interface, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- PerSiVal: deep neural networks for pervasive simulation of an activation-driven continuum-mechanical upper limb model.Medical & biological engineering & computing · 2026Article
- Different physiologic biomechanical metrics correlate with aortic diameter increases in normal maturation compared to aneurysm progression in mice.Journal of the mechanical behavior of biomedical materials · 2025Article
- The next frontier in healthcare: perspectives and discussion on building trust and societal acceptance of digital humans in the essential framework of impact biomechanics.Frontiers in bioengineering and biotechnology · 2025Review
- FEBio FINESSE: An Open-Source Finite Element Simulation Approach to Estimate In Vivo Heart Valve Strains Using Shape Enforcement.Annals of biomedical engineering · 2025Article
- Democratizing biomedical simulation through automated model discovery and a universal material subroutine.Computational mechanics · 2025Article
- The mechanical and sensory signature of plant-based and animal meat.NPJ science of food · 2024Article
- Review of Machine Learning Techniques in Soft Tissue Biomechanics and Biomaterials.Cardiovascular engineering and technology · 2024Review
- Data-driven continuum damage mechanics with built-in physics.Extreme Mechanics Letters · 2024Article
- Benchmarking physics-informed frameworks for data-driven hyperelasticity.Computational mechanics · 2024Article
- Synergistic Integration of Deep Neural Networks and Finite Element Method with Applications of Nonlinear Large Deformation Biomechanics.Computer methods in applied mechanics and engineering · 2023Article
- The Potential of Deep Learning to Advance Clinical Applications of Computational Biomechanics.Bioengineering (Basel, Switzerland) · 2023Review
- G2Φnet: Relating genotype and biomechanical phenotype of tissues with deep learning.PLoS computational biology · 2022Article
- Predicting the trabecular bone apparent stiffness tensor with spherical convolutional neural networks.Bone reports · 2022Article
- A fluid-structure interaction model accounting arterial vessels as a key part of the blood-flow engine for the analysis of cardiovascular diseases.Frontiers in bioengineering and biotechnology · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The constitutive modelling of soft biological tissues has rapidly gained attention over the last 20 years. Current constitutive models can describe the mechanical properties of arterial tissue. Predicting these properties from microstructural information, however, remains an elusive goal. To address this challenge, we are introducing a novel hybrid modelling framework that combines advanced theoretical concepts with deep learning. It uses data from mechanical tests, histological analysis and images from second-harmonic generation. In this first proof of concept study, our hybrid modelling framework is trained with data from 27 tissue samples only. Even such a small amount of data is sufficient to be able to predict the stress-stretch curves of tissue samples with a median coefficient of determination of
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