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Uncertainty-aware deep-learning model for prediction of supratentorial hematoma expansion from admission non-contrast head computed tomography scan

npj Digital Medicine(2024)10.1038/s41746-024-01007-wSource: DataRank Database

Uncertainty-aware deep-learning model for prediction of supratentorial hematoma expansion from admission non-contrast head computed tomography scan is a research paper published in npj Digital Medicine (2024). On theSindex it has a DataRank of 0. It has been cited 25 times.

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Open Access25 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (20 grants)Impact (FWCI 7.62)OA: goldTopics (27)IDs (PubMed, PMC, OpenAlex)Annotations (1)SDGs (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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Authors (15)

Tal Zeevi ORCID,Stefan P. Haider ORCID,Gaby Abou Karam ORCID,Elisa R. Berson ORCID,Hishan Tharmaseelan ORCID

Live enrichment

PubMed:38321131 PMC:PMC10847454 OpenAlex:https://openalex.org/W4391573802

NINDS NIH HHS

Grant: K23 NS110980

NINDS NIH HHS

Grant: K23 NS118056

NINDS NIH HHS

Grant: R03 NS112859

NCATS NIH HHS

Grant: UL1 TR001863

NIA NIH HHS

Grant: P30 AG021342

NINDS NIH HHS

Grant: U24 NS107136

NINR NIH HHS

Grant: R01 NR018335

NINDS NIH HHS

Grant: U01 NS106513

NHLBI NIH HHS

Grant: T35 HL007649

NINDS NIH HHS

Grant: U24 NS107215

Doris Duke Charitable Foundation

Grant: 2020097

NIA NIH HHS

Grant: K76 AG059992

National Institutes of Health

Grant: 5U24NS107215-07

Southern New England Partnership In Stroke Research, Innovation and Treatment (SPIRIT)

National Institutes of Health

Grant: 5P30AG021342-13

Information Dissemination Core

National Institutes of Health

Grant: 5K23NS118056-04

Radiomics signatures and patient outcomes in intracerebral hemorrhage

National Institutes of Health

Grant: 5U01NS106513-04

Anticoagulation in ICH Survivors for Prevention and Recovery (ASPIRE)

National Institutes of Health

Grant: 5R01NR018335-05

The Recovery in Stroke Using PAP (RISE UP) Study

National Institutes of Health

Grant: 5R03NS112859-02

Intensive Blood Pressure Reduction in Deep Intracerebral Hemorrhage

National Institutes of Health

Grant: 1K76AG059992-01

Genetic analyses of radiological severity, short-term functional outcome and long-term health status in spontaneous intracerebral hemorrhage

National Institutes of Health

Grant: 5U24NS107136-03

Yale Clinical Site: Investigations For Improved Neurological Treatments at Yale (INFINITY)

FWCI

7.62

Citation Percentile

1.0%

Citation Trend

2024

2025

2026

goldLicense: cc-by

journalhttps://www.nature.com/articles/s41746-024-01007-w.pdf

publisherhttps://www.nature.com/articles/s41746-024-01007-w.pdf

publisherhttps://www.nature.com/articles/s41746-024-01007-w

journalhttps://doi.org/10.1038/s41746-024-01007-w

repositoryhttps://pubmed.ncbi.nlm.nih.gov/38321131

Fields of Study

Intracerebral and Subarachnoid Hemorrhage ResearchAcute Ischemic Stroke ManagementNeurosurgical Procedures and Complications0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

Confidence intervalArtificial intelligenceReceiver operating characteristicContrast (vision)MedicineLow ConfidenceHematomaIntracerebral hemorrhageComputed tomographyDeep learningMachine learningDropout (neural networks)Area under the curveRadiologyComputer scienceInternal medicinePsychologyStrokeComputer applications to medicine. Medical informaticsR858-859.7Brain imagingArticle

Sustainable Development Goals

SDG 3: 3. Good healthSDG 0: Quality Education

Uncertainty-aware deep-learning model for prediction of supratentorial hematoma expansion from admission non-contrast head computed tomography scan

FAIR Checklist

Authors (15)

Funding (20 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)