Pilot corpus: NIH-funded biomedical datasets. Any DOI can be scored on demand — network effects sharpen as coverage grows.

Using generative AI to investigate medical imagery models and datasets

EBioMedicine(2024)10.1016/j.ebiom.2024.105075Source: DataRank Database

Using generative AI to investigate medical imagery models and datasets is a research paper published in EBioMedicine (2024). On theSindex it has a DataRank of 0. It has been cited 56 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access56 citations

Download PDF

Cite:

Linked data & code

doi

DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (6 grants)Impact (FWCI 14.34)OA: goldTopics (46)IDs (PubMed, PMC, OpenAlex)Annotations (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)

FAIR checklist signals are shown for context only and do not affect DataRank scoring.

Run a calibrated FAIR evaluation for this paper →

We only score data papers we can read in full — never from an abstract alone.

Authors (16)

Doron Stupp ORCID,Ilana Traynis,Heather Cole-Lewis ORCID,Chloe R. Bennett,Courtney R. Lyles ORCID

Live enrichment

PubMed:38565004 PMC:PMC10993140 OpenAlex:https://openalex.org/W4393376341

NCATS NIH HHS

Grant: UL1 TR001855

NCATS NIH HHS

Grant: UL1 TR000130

National Institutes of Health

Grant: 3UL1TR001855-06A1S1

Southern California Clinical and Translational Science Institute

National Institutes of Health

Grant: 3UL1TR000130-05S2

Southern California Clinical and Translational Science Institute

National Center for Advancing Translational Sciences

National Institutes of Health

FWCI

14.34

Citation Percentile

1.0%

Citation Trend

2024

2025

2026

goldLicense: CC BY NC

journalhttp://www.thelancet.com/article/S2352396424001105/pdf

publisherhttp://www.thelancet.com/article/S2352396424001105/pdf

publisherhttps://api.elsevier.com/content/article/PII:S2352396424001105?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S2352396424001105?httpAccept=text/plain

journalhttps://doi.org/10.1016/j.ebiom.2024.105075

Fields of Study

Retinal Imaging and AnalysisExplainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education02 engineering and technology0202 electrical engineering, electronic engineering, information engineeringHumansAlgorithmsCardiomegalyCataractFundus OculiArtificial Intelligence

MeSH Terms

AlgorithmsArtificial IntelligenceCataractFundus OculiCardiomegalyHumans

Keywords

Computer scienceCounterfactual thinkingClassifier (UML)Artificial intelligenceMachine learningVisualizationWorkflowGenerative modelGenerative grammarTask (project management)InterpretabilityDeep LearningMedical ImageryExplainabilityGenerative AiFOS: Computer and information sciencesComputer Science - Machine LearningFundus OculiComputer Vision and Pattern Recognition (cs.CV)Image and Video Processing (eess.IV)Computer Science - Computer Vision and Pattern RecognitionCardiomegalyArticlesElectrical Engineering and Systems Science - Image and Video ProcessingCataractMachine Learning (cs.LG)FOS: Electrical engineering, electronic engineering, information engineeringHumansAlgorithms

Using generative AI to investigate medical imagery models and datasets

FAIR Checklist

Authors (16)

Funding (6 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)