Manifold learning based data-driven modeling for soft biological tissues

Volume: 117, Pages: 110124 - 110124
Published: Mar 1, 2021
Abstract
Data-driven modeling directly utilizes experimental data with machine learning techniques to predict a material's response without the necessity of using phenomenological constitutive models. Although data-driven modeling presents a promising new approach, it has yet to be extended to the modeling of large-deformation biological tissues. Herein, we extend our recent local convexity data-driven (LCDD) framework (He and Chen, 2020) to model the...
Paper Details
Title
Manifold learning based data-driven modeling for soft biological tissues
Published Date
Mar 1, 2021
Volume
117
Pages
110124 - 110124
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.