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Non-invasive Inference of Thrombus Material Properties with Physics-Informed Neural Networks
We employ physics-informed neural networks (PINNs) to infer properties of biological materials using synthetic data. In particular, we successfully apply PINNs on inferring permeability and viscoelastic modulus from thrombus deformation data, which can be described by the fourth-order Cahn-Hilliard...
में बचाया:
| में प्रकाशित: | Comput Methods Appl Mech Eng |
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| मुख्य लेखकों: | , , , |
| स्वरूप: | Artigo |
| भाषा: | Inglês |
| प्रकाशित: |
2020
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| विषय: | |
| ऑनलाइन पहुंच: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7785048/ https://ncbi.nlm.nih.gov/pubmed/33414569 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.cma.2020.113603 |
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