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Using machine learning in the prediction of symptomatic venous thromboembolism following ankle fracture

Foot and Ankle Surgery(2023)10.1016/j.fas.2023.10.003Source: DataRank Database

Using machine learning in the prediction of symptomatic venous thromboembolism following ankle fracture is a research paper published in Foot and Ankle Surgery (2023). On theSindex it has a DataRank of 0. It has been cited 12 times.

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12 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (5 grants)Impact (FWCI 2.75)OA: closedTopics (36)IDs (PubMed, OpenAlex)SDGs (1)

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Findable (1/2)

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Accessible (0/2)

Interoperable (0/2)

Reusable (0/3)

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Authors (8)

Bardiya Akhbari ORCID,Noopur Ranganathan ORCID,David Shin ORCID,Hamid Ghaednia ORCID,Soheil Ashkani‐Esfahani ORCID

Live enrichment

PubMed:38193887 OpenAlex:https://openalex.org/W4387639306

National Institutes of Health

Grant: UL1 TR002541

American Orthopaedic Foot and Ankle Society

Grant: 2021–13303-E

Harvard Catalyst

Harvard University

National Center for Advancing Translational Sciences

FWCI

2.75

Citation Percentile

0.9%

Citation Trend

2024

2025

2026

closedLicense: https://www.elsevier.com/legal/tdmrep-license

publisherhttps://api.elsevier.com/content/article/PII:S1268773123001911?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S1268773123001911?httpAccept=text/plain

journalhttps://doi.org/10.1016/j.fas.2023.10.003

repositoryhttps://pubmed.ncbi.nlm.nih.gov/38193887

Fields of Study

Venous Thromboembolism Diagnosis and ManagementPeripheral Artery Disease ManagementDiagnosis and Treatment of Venous DiseasesHumansVenous ThromboembolismAnkle FracturesCase-Control StudiesRetrospective StudiesReproducibility of ResultsRisk FactorsAnticoagulants

MeSH Terms

AnticoagulantsHumansRetrospective StudiesRisk FactorsReproducibility of ResultsCase-Control StudiesVenous ThromboembolismAnkle Fractures

Keywords

MedicineAnkleOrthopedic surgeryIncidence (geometry)Receiver operating characteristicWarfarinStroke (engine)Venous thromboembolismEmergency medicineSurgeryInternal medicineThrombosisArtificial intelligenceScreeningPreventionPulmonary embolismDeep Venous Thrombosis

Sustainable Development Goals

SDG 0: Good health and well-being

Using machine learning in the prediction of symptomatic venous thromboembolism following ankle fracture

FAIR Checklist

Authors (8)

Funding (5 grants)

Impact

Open Access

Topics