ArticleJournal of the mechanical behavior of biomedical materials2024
Accuracy meets simplicity: A constitutive model for heterogenous brain tissue.
Article in Journal of the mechanical behavior of biomedical materials, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- Optimal experimental design for repeatable hyperelastic material characterization.Journal of the mechanical behavior of biomedical materials · 2025Article
- Mechanical characterization of brain tissue: experimental techniques, human testing considerations, and perspectives.Acta biomaterialia · 2025Review
- Exploring hyperelastic material model discovery for human brain cortex: Multivariate analysis vs. artificial neural network approaches.Journal of the mechanical behavior of biomedical materials · 2025Article
- Article
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- Automated data-driven discovery of material models based on symbolic regression: A case study on the human brain cortex.Acta biomaterialia · 2024Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
We present a general, hyperelastic, stretch-based potential that shows promise for modeling the mechanics of brain tissue. A specific four-parameter model derived from this general potential outperforms alternative models, such as the modified Ogden model, the Gent model, Demiray model, and machine-learning models, in capturing brain tissue elasticity. Specifically, the stretch-based model achieved R
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.