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Developing a Reproducible Radiomics Model for Diagnosis of Active Crohn’s Disease on CT Enterography Across Annotation Variations and Acquisition Differences

Journal of Imaging Informatics in Medicine(2024)10.1007/s10278-024-01303-7Source: DataRank Database

Developing a Reproducible Radiomics Model for Diagnosis of Active Crohn’s Disease on CT Enterography Across Annotation Variations and Acquisition Differences is a research paper published in Journal of Imaging Informatics in Medicine (2024). On theSindex it has a DataRank of 0. It has been cited 3 times.

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Open Access3 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (18 grants)Impact (FWCI 1.05)OA: greenTopics (54)IDs (PubMed, PMC, OpenAlex)SDGs (1)

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Context only (not used in score)

Findable (1/2)

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Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (6)

Pavithran Pattiam Giriprakash,Alain Rizk ORCID,Jacob A. Kurowski ORCID,Satish E. Viswanath ORCID,Namita Gandhi ORCID

Live enrichment

PubMed:39466507 PMC:PMC12092320 OpenAlex:https://openalex.org/W4403829176

National Institute of Diabetes and Digestive and Kidney Diseases

Grant: 1F31DK130587-01A1

Radiomics-based Risk Prediction for Therapy Selection in Crohn’s Disease via MRI

National Cancer Institute

Grant: 1U01CA248226-01

RadxTools for assessing tumor treatment response on imaging

National Cancer Institute

Grant: 1R01CA280981-01A1

Novel radiomic signatures for treatment response to neoadjuvant therapy in rectal cancers

National Institute of Nursing Research

Grant: 1R01NR019585-01A1

OPtimizing Technology to Improve Medication Adherence and BP Control (OPTIMA-BP).

National Heart, Lung, and Blood Institute

Grant: 1R01HL165218-01A1

Cardiovascular risk from comprehensive evaluation of the CT calcium score exam

National Science Foundation

Grant: Award# 2320952

DOD Peer Reviewed Cancer Research Program

Grant: W81XWH-21-1-0345

DOD Peer Reviewed Cancer Research Program

Grant: W81XWH 19-1-0668

DOD Peer Reviewed Cancer Research Program

Grant: W81XWH-21-1-0725

U.S. Department of Veterans Affairs

Grant: 1I01BX006439-01

Artificial Intelligence Imaging Predictors for Rectal Cancer Management

NIDDK NIH HHS

Grant: F31 DK130587

BLRD VA

Grant: I01 BX006439

NCI NIH HHS

Grant: U01 CA248226

NCI NIH HHS

Grant: R01 CA280981

NHLBI NIH HHS

Grant: R01 HL165218

NINR NIH HHS

Grant: R01 NR019585

National Science Foundation

Grant: 2320952

Collaborative Research: SCIPE: Interdisciplinary Research Support Community for Artificial Intelligence and Data Sciences

Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity

FWCI

1.05

Citation Percentile

0.8%

Citation Trend

2025

2026

greenLicense: Springer Nature TDM

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC12092320/pdf/10278_2024_Article_1303.pdf

publisherhttps://link.springer.com/content/pdf/10.1007/s10278-024-01303-7.pdf

publisherhttps://link.springer.com/article/10.1007/s10278-024-01303-7/fulltext.html

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/12092320

Fields of Study

Radiomics and Machine Learning in Medical ImagingColorectal Cancer Surgical TreatmentsGastric Cancer Management and Outcomes03 medical and health sciences0302 clinical medicineHumansCrohn DiseaseMaleFemaleTomography, X-Ray ComputedReproducibility of ResultsRetrospective StudiesAdultMiddle AgedYoung AdultRadiographic Image Interpretation, Computer-AssistedRadiomics

MeSH Terms

RadiomicsAdultCrohn DiseaseFemaleHumansMaleMiddle AgedRadiographic Image Interpretation, Computer-AssistedRetrospective StudiesTomography, X-Ray ComputedReproducibility of ResultsYoung Adult

Keywords

RadiomicsCrohn's diseaseMedicineAnnotationCrohn diseaseRadiologyDiseaseMedical physicsComputer scienceArtificial intelligencePathologyCrohn’s DiseaseIterative ReconstructionCteReduced DoseMaleAdultReproducibility of ResultsMiddle AgedYoung AdultHumansRadiographic Image Interpretation, Computer-AssistedFemaleTomography, X-Ray ComputedRetrospective Studies

Sustainable Development Goals

SDG 0: Zero hunger