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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(2024)10.1016/j.actbio.2024.09.005Source: DataRank Database

Automated data-driven discovery of material models based on symbolic regression: A case study on the human brain cortex is a research paper published in Acta Biomaterialia (2024). On theSindex it has a DataRank of 0. It has been cited 19 times.

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Open Access19 citations

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Automated Data-Driven Discovery of Material Models Based on Symbolic Regression: A Case Study on Human Brain Cortex · arXiv

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (8 grants)Impact (FWCI 1.73)OA: greenTopics (42)Linked Datasets (1)DataCite Reuse (1)IDs (PubMed, PMC, OpenAlex)

FAIR Checklist

Context only (not used in score)

Findable (2/2)

Has DOI
Indexed in repositories

Accessible (1/2)

Open Access

Interoperable (2/2)

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Linked datasets

Reusable (0/3)

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Authors (5)

Xianyan Chen ORCID,Taotao Wu ORCID,Ellen Kuhl ORCID,Xianqiao Wang ORCID,Jixin Hou ORCID

Live enrichment

PubMed:39299620 PMC:PMC12205916 OpenAlex:https://openalex.org/W4402558995

National Science Foundation

Grant: IIS-2011369

NINDS NIH HHS

Grant: R01 NS135574

NIDDK NIH HHS

Grant: R01 DK135574

National Science Foundation

Grant: 2320933

Automated Model Discovery for Soft Matter

National Science Foundation

Grant: 2011369

CRCNS Research Proposal: Exploring the Mechanism of 3-Hinge Gyral Formation and its Role in Brain Networks

National Institutes of Health

Grant: 1R01NS135574-01

SCH: Using Data-Driven Computational Biomechanics to Disentangle Brain Structural Commonality, Variability, and Abnormality in ASD

Foundation for the National Institutes of Health

National Institutes of Health

FWCI

1.73

Citation Percentile

0.9%

Citation Trend

2024

2025

2026

greenLicense: Elsevier TDM

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC12205916/pdf/nihms-2088906.pdf

publisherhttps://api.elsevier.com/content/article/PII:S174270612400521X?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S174270612400521X?httpAccept=text/plain

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/12205916

Fields of Study

Machine Learning in Materials ScienceMedical Image Segmentation TechniquesImage Processing and 3D Reconstruction02 engineering and technology0202 electrical engineering, electronic engineering, information engineering

MeSH Terms

AlgorithmsCerebral CortexElasticityHumansModels, BiologicalRegression Analysis

Keywords

Regression analysisRegressionCortex (anatomy)Artificial intelligenceComputer scienceMaterials scienceNeuroscienceBiomedical engineeringMachine learningStatisticsPsychologyMathematicsEngineeringPolyconvexityHyperelasticityConstitutive ModelingSymbolic RegressionModel DiscoveryComputer Science - Symbolic ComputationCerebral CortexFOS: Computer and information sciencesQuantitative Biology - Tissues and OrgansSymbolic Computation (cs.SC)Quantitative Biology - Quantitative MethodsModels, BiologicalElasticityFOS: Biological sciencesHumansTissues and Organs (q-bio.TO)AlgorithmsQuantitative Methods (q-bio.QM)

Automated Data-Driven Discovery of Material Models Based on Symbolic Regression: A Case Study on Human Brain Cortex

10.48550/arxiv.2402.05238arXiv