Different Types of Constitutive Parameters Red Blood Cell Membrane Based on Machine Learning and FEM

DOI10.1142/S0219876222500578OpenAlexW4313248803MaRDI QIDQ6173082

Xinyu Wei, Unnamed Author, Chuan Tian, Baoyou Liu, Unnamed Author

Publication date: 21 July 2023

Published in: International Journal of Computational Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0219876222500578

zbMATH Keywords

finite element analysisred blood cellsinverse identificationextreme gradient boostingtwo-way deepnets

Mathematics Subject Classification ID

Mechanics of deformable solids (74-XX) Biology and other natural sciences (92-XX)

Cites Work

• Greedy function approximation: A gradient boosting machine.
• A fictitious domain method with a hybrid cell model for simulating motion of cells in fluid flow
• Systematic coarse-graining of spectrin-level red blood cell models
• A spectral boundary integral method for flowing blood cells
• Dynamical Modes of Deformed Red Blood Cells and Lipid Vesicles in Flows
• FEA-AI and AI-AI: Two-Way Deepnets for Real-Time Computations for Both Forward and Inverse Mechanics Problems

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