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

Detecting diabetic retinopathy through machine learning on electronic health record data from an urban, safety net healthcare system

JAMIA Open(2021)10.1093/jamiaopen/ooab066Source: DataRank Database

Detecting diabetic retinopathy through machine learning on electronic health record data from an urban, safety net healthcare system is a research paper published in JAMIA Open (2021). On theSindex it has a DataRank of 0. It has been cited 24 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access24 citations

Download PDF

Cite:

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 (4 grants)Impact (FWCI 2.41)OA: goldTopics (46)IDs (PubMed, PMC, OpenAlex)SDGs (3)

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 (8)

Meghal Gandhi,Martin Lee ORCID,Senait Teklehaimanot,Lauren P. Daskivich ORCID,David Hindman

Live enrichment

PubMed:34423259 PMC:PMC8374369 OpenAlex:https://openalex.org/W3194761804

NLM NIH HHS

Grant: R01 LM012309

National Institutes of Health

Grant: 3R01LM012309-04S2

Predicting Diabetic Retinopathy from Risk Factor Data and Digital Retinal Images

National Institutes of Health

Grant: 3UL1TR001855-06A1S1

Southern California Clinical and Translational Science Institute

National Institutes of Health

Grant: 3UL1TR001881-01S2

UCLA Clinical Translational Science Institute

FWCI

2.41

Citation Percentile

0.9%

Citation Trend

2022

2023

2024

2025

2026

goldLicense: cc-by

journalhttps://academic.oup.com/jamiaopen/article-pdf/4/3/ooab066/39805206/ooab066.pdf

publisherhttps://academic.oup.com/jamiaopen/article-pdf/4/3/ooab066/39805206/ooab066.pdf

publisherhttp://academic.oup.com/jamiaopen/article-pdf/4/3/ooab066/39805206/ooab066.pdf

journalhttps://doi.org/10.1093/jamiaopen/ooab066

repositoryhttps://pubmed.ncbi.nlm.nih.gov/34423259

Fields of Study

Retinal Imaging and AnalysisRetinal Diseases and TreatmentsArtificial Intelligence in Healthcare03 medical and health sciences0302 clinical medicine

Keywords

MedicineArtificial intelligenceMachine learningDiabetic retinopathyHealth careDiabetes mellitusTest setGuidelineClassifier (UML)Deep learningComputer sciencePathologySafety Net ProvidersDiabetic Retinopathy Diagnosis610Health Disparities (rcdc)Research and ApplicationsClinical Research (rcdc)Clinical ResearchHealth Services and SystemsHealth Sciences616Machine Learning and Artificial IntelligenceHealth Services (rcdc)Metabolic and endocrineNeurosciences (rcdc)42 Health Sciences (for-2020)Networking and Information Technology R&D (NITRD) (rcdc)3 Good Health and Well Being (sdg)4203 Health services and systems (for-2020)Diabetes4.1 Discovery and preclinical testing of markers and technologies (hrcs-rac)NeurosciencesHealth Services4.1 Discovery and preclinical testing of markers and technologiesHealth DisparitiesGood Health and Well BeingNetworking and Information Technology R&D (NITRD)Metabolic and endocrine (hrcs-hc)Diabetes (rcdc)Machine Learning and Artificial Intelligence (rcdc)

Sustainable Development Goals

SDG 3: 3. Good healthSDG 11: 11. SustainabilitySDG 0: Sustainable cities and communities