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Deep learning models using intracranial and scalp EEG for predicting sedation level during emergence from anaesthesia

BJA Open(2024)10.1016/j.bjao.2024.100347Source: DataRank Database

Deep learning models using intracranial and scalp EEG for predicting sedation level during emergence from anaesthesia is a research paper published in BJA Open (2024). On theSindex it has a DataRank of 0.269. It has been cited 5 times.

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0.269DataRank · unranked

Scored on demand from live citation data

Open Access5 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (1 grants)OA: goldTopics (10)IDs (PubMed, PMC)Annotations (2)

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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DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.269

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

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Authors (9)

David Purger ORCID,Sarah L. Eagleman ORCID,Casey H. Halpern ORCID,Vivek Buch ORCID,Samantha Gaston

Live enrichment

PubMed:40018289 PMC:PMC11867133

National Institutes of Health

Grant: 1K99GM140215-01

Intracranial cortical network connectivity underlying complexity changes during anesthetic emergence

goldLicense: cc-by-nc-nd

publisherhttps://www.bjaopen.org/article/S2772-6096(24)00091-1/pdf

publisherhttps://api.elsevier.com/content/article/PII:S2772609624000911?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S2772609624000911?httpAccept=text/plain

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC11867133/pdf/main.pdf

repositoryhttps://doaj.org/article/eb147f953852463999ddcbcaa056f557

Fields of Study

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

Keywords

ElectroencephalographyDeep LearningPrediction ModellingDepth Of SedationIntracranial ElectroencephalographyAnesthesiologyRD78.3-87.3Original Research Article

Deep learning models using intracranial and scalp EEG for predicting sedation level during emergence from anaesthesia

FAIR Checklist

DataRank Breakdown

Authors (9)

Funding (1 grants)

Open Access

Topics

Annotations (Europe PMC)