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MRI-based radiomic feature analysis of end-stage liver disease for severity stratification

International Journal of Computer Assisted Radiology and Surgery(2021)10.1007/s11548-020-02295-9Source: DataRank Database

MRI-based radiomic feature analysis of end-stage liver disease for severity stratification is a research paper published in International Journal of Computer Assisted Radiology and Surgery (2021). On theSindex it has a DataRank of 0. It has been cited 11 times.

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Open Access11 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (10 grants)Impact (FWCI 1.20)OA: hybridTopics (82)IDs (PubMed, OpenAlex)SDGs (4)

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 (8)

Jordan Sack ORCID,Michael Halle ORCID,Jan Hendrik Moltz ORCID,April Wall,Anna Rutherford

Live enrichment

PubMed:33646521 OpenAlex:https://openalex.org/W3133754084

National Institutes of Health

Grant: P41 EB015902

National Institutes of Health

Grant: P41 EB015898

National Institutes of Health

Grant: U24 CA180918

National Institutes of Health

Grant: NIH 5 T32 DK007533-35

National Institutes of Health

Grant: 5U24CA180918-02

Quantitative Image Informatics for Cancer Research (QIICR)

National Institutes of Health

Grant: 5T32DK007533-19

ALIMENTARY TRACT RESEARCH IN HEALTH AND DISEASE

National Institutes of Health

Grant: 5P41EB015902-20

Neuroimaging Analysis Center (NAC)

National Institutes of Health

Grant: 8P41EB015898-08

IMAGE GUIDED THERAPY CENTER

NIDDK NIH HHS

Grant: T32 DK007533

NIBIB NIH HHS

Grant: P41 EB028741

FWCI

1.20

Citation Percentile

0.8%

Citation Trend

2022

2023

2024

hybridLicense: cc-by

journalhttps://link.springer.com/content/pdf/10.1007/s11548-020-02295-9.pdf

publisherhttps://link.springer.com/content/pdf/10.1007/s11548-020-02295-9.pdf

publisherhttp://link.springer.com/content/pdf/10.1007/s11548-020-02295-9.pdf

publisherhttp://link.springer.com/article/10.1007/s11548-020-02295-9/fulltext.html

journalhttps://doi.org/10.1007/s11548-020-02295-9

Fields of Study

Hepatocellular Carcinoma Treatment and PrognosisLiver Disease Diagnosis and TreatmentRadiomics and Machine Learning in Medical Imaging03 medical and health sciences0302 clinical medicineAdultAgedAlgorithmsArea Under CurveCarcinoma, HepatocellularEnd Stage Liver DiseaseFemaleHumansImage Processing, Computer-AssistedLiverLiver CirrhosisLiver NeoplasmsMagnetic Resonance ImagingMaleMiddle AgedPrognosisRetrospective StudiesSeverity of Illness IndexSpleen

MeSH Terms

AdultAgedAlgorithmsFemaleCarcinoma, HepatocellularHumansImage Processing, Computer-AssistedLiverLiver CirrhosisLiver NeoplasmsMagnetic Resonance ImagingMaleMiddle AgedPrognosisRetrospective StudiesSeverity of Illness IndexSpleenArea Under CurveEnd Stage Liver Disease

Keywords

MedicineDecompensationCirrhosisHepatocellular carcinomaLiver diseaseCohortInternal medicineLogistic regressionModel for End-Stage Liver DiseaseRetrospective cohort studyStage (stratigraphy)RadiologyGastroenterologyLiver transplantationTransplantationAdultLiver CirrhosisMaleCarcinoma, HepatocellularLiver NeoplasmsMiddle AgedPrognosisMagnetic Resonance ImagingSeverity of Illness IndexEnd Stage Liver DiseaseLiverArea Under CurveImage Processing, Computer-AssistedHumansOriginal ArticleFemaleAlgorithmsSpleenAgedRetrospective StudiesBiomarkerClinical decision supportEnd-stage liver diseaseRadiomics

Sustainable Development Goals

SDG 3: 3. Good healthSDG 10: 10. No inequalitySDG 0: Peace, Justice and strong institutionsSDG 0: Reduced inequalities