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Using deep-learning based segmentation to enable spatial evaluation of knee osteoarthritis (SEKO) in rodent models

Osteoarthritis and Cartilage(2025)10.1016/j.joca.2025.02.787Source: DataRank Database

Using deep-learning based segmentation to enable spatial evaluation of knee osteoarthritis (SEKO) in rodent models is a research paper published in Osteoarthritis and Cartilage (2025). On theSindex it has a DataRank of 0. It has been cited 4 times.

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4 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (7 grants)Impact (FWCI 3.44)OA: closedTopics (31)IDs (PubMed, OpenAlex)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (0/2)

Interoperable (0/2)

Reusable (0/3)

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Authors (5)

Justin Joseph,Andrew Jensen ORCID,Scott A. Banks ORCID,Kyle D. Allen ORCID,Jacob L. Griffith ORCID

Live enrichment

PubMed:40139644 OpenAlex:https://openalex.org/W4408800540

National Science Foundation Graduate Research Fellowship Program

Grant: DGE-1842473

National Institute of Arthritis and Musculoskeletal and Skin Diseases

Grant: R01AR071431-04S2

National Institute of Arthritis and Musculoskeletal and Skin Diseases

Grant: UC2AR082196

NIAMS NIH HHS

Grant: R01 AR071431

University of Florida

National Science Foundation

National Institutes of Health

FWCI

3.44

Citation Percentile

0.9%

Citation Trend

2025

2026

closedLicense: http://www.elsevier.com/open-access/userlicense/1.0/

publisherhttps://api.elsevier.com/content/article/PII:S1063458425008672?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S1063458425008672?httpAccept=text/plain

journalhttps://doi.org/10.1016/j.joca.2025.02.787

repositoryhttps://pubmed.ncbi.nlm.nih.gov/40139644

Fields of Study

Osteoarthritis Treatment and MechanismsTotal Knee Arthroplasty OutcomesMedical Image Segmentation Techniques

MeSH Terms

Deep LearningAnimalsArthritis, ExperimentalCartilage, ArticularDisease Models, AnimalKnee JointBone RemodelingOsteoarthritis, KneeMiceRats

Keywords

OsteoarthritisSegmentationArtificial intelligenceComputer scienceRodentCartographyPhysical medicine and rehabilitationMedicineGeographyBiologyPathologyEcologyKnee OsteoarthritisBone RemodelingPreclinical ModelsQuantitative HistologyCartilage DamageConvolutional Neural Networks

Using deep-learning based segmentation to enable spatial evaluation of knee osteoarthritis (SEKO) in rodent models

FAIR Checklist

Authors (5)

Funding (7 grants)

Impact

Open Access

Topics