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Detection of Obstructive Sleep Apnoea Using Features Extracted From Segmented Time-Series ECG Signals With a One Dimensional Convolutional Neural Network

IEEE Access(2023)10.1109/access.2023.3346689Source: DataRank Database

Detection of Obstructive Sleep Apnoea Using Features Extracted From Segmented Time-Series ECG Signals With a One Dimensional Convolutional Neural Network is a research paper published in IEEE Access (2023). On theSindex it has a DataRank of 0. It has been cited 4 times.

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0DataRank · unranked

Scored on demand from live citation data

Open Access4 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Impact (FWCI 0.63)OA: goldTopics (17)IDs (PubMed, OpenAlex)SDGs (1)

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)

Denis Reilly ORCID,Paul Fergus ORCID,Carl Chalmers ORCID,Steven Thompson ORCID

Live enrichment

PubMed:19767382 OpenAlex:https://openalex.org/W4390204376

FWCI

0.63

Citation Percentile

0.7%

Citation Trend

2024

2025

goldLicense: cc-by

journalhttps://ieeexplore.ieee.org/ielx7/6287639/6514899/10373019.pdf

publisherhttps://ieeexplore.ieee.org/ielx7/6287639/6514899/10373019.pdf

publisherhttp://xplorestaging.ieee.org/ielx7/6287639/10380310/10373019.pdf?arnumber=10373019

journalhttps://doi.org/10.1109/access.2023.3346689

repositoryhttps://orcid.org/0009-0004-6796-3028

Fields of Study

Obstructive Sleep Apnea ResearchEEG and Brain-Computer InterfacesSleep and Work-Related Fatigue

Keywords

Softmax functionSupport vector machineComputer scienceArtificial intelligencePattern recognition (psychology)Convolutional neural networkMultilayer perceptronRandom forestClassifier (UML)Sensitivity (control systems)Precision and recallPoolingF1 scoreArtificial neural network

Sustainable Development Goals

SDG 0: Life in Land