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Detecting Cardiac Abnormalities from 12-lead ECG Signals Using Feature Extraction, Dimensionality Reduction, and Machine Learning Classification

Computing in cardiology(2020)10.22489/cinc.2020.217Source: DataRank Database

Detecting Cardiac Abnormalities from 12-lead ECG Signals Using Feature Extraction, Dimensionality Reduction, and Machine Learning Classification is a research paper published in Computing in cardiology (2020). On theSindex it has a DataRank of 0. It has been cited 1 time.

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0DataRank · unranked

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Open Access1 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: bronzeTopics (2)IDs (PubMed)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (4)

J. Chase McGlinn,Muhammad Rizwan ORCID,Bradley M. Whitaker ORCID,Garrett Perkins

Live enrichment

PubMed:23304386

National Institutes of Health

Grant: 5P20GM103474-13

Montana INBRE II: A Multidisciplinary Research Network

bronze

publisherhttps://doi.org/10.22489/cinc.2020.217

Fields of Study

0202 electrical engineering, electronic engineering, information engineering02 engineering and technology