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Biometric Contrastive Learning for Data-Efficient Deep Learning from Electrocardiographic Images

medRxiv(2023)10.1101/2023.09.13.23295494Source: DataRank Database

Biometric Contrastive Learning for Data-Efficient Deep Learning from Electrocardiographic Images is a research paper published in medRxiv (2023). On theSindex it has a DataRank of 0. It has been cited 5 times.

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Open Access5 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (1 grants)OA: greenTopics (15)IDs (PubMed, OpenAlex)

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Accessible (1/2)

Open Access

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Reusable (0/3)

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Authors (7)

Akshay Khunte ORCID,Gregory Holste ORCID,Bobak J. Mortazavi ORCID,Zhangyang Wang ORCID,Evangelos K. Oikonomou ORCID

Live enrichment

PubMed:37745527 OpenAlex:https://openalex.org/W4386734867

National Institutes of Health

Grant: 5K23HL153775-05

Evaluating and Improving Utilization of Evidence-Based Medical Therapy in Patients with Heart Failure using Automated Tools in the Electronic Health Record

greenLicense: cc-by-nc

repositoryhttps://www.medrxiv.org/content/medrxiv/early/2023/09/14/2023.09.13.23295494.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2023.09.13.23295494

repositoryhttps://doi.org/10.1101/2023.09.13.23295494

repositoryhttps://pubmed.ncbi.nlm.nih.gov/37745527

Fields of Study

ECG Monitoring and AnalysisAtrial Fibrillation Management and OutcomesCardiac electrophysiology and arrhythmias0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

BiometricsArtificial intelligenceComputer scienceDeep learningPattern recognition (psychology)ElectrocardiographyBiometryAtrial FibrillationHumansArticle