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Improving the Identification of Diabetic Retinopathy and Related Conditions in the Electronic Health Record Using Natural Language Processing Methods

Ophthalmology Science(2024)10.1016/j.xops.2024.100578Source: DataRank Database

Improving the Identification of Diabetic Retinopathy and Related Conditions in the Electronic Health Record Using Natural Language Processing Methods is a research paper published in Ophthalmology Science (2024). On theSindex it has a DataRank of 0. It has been cited 7 times.

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Open Access7 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (4 grants)Impact (FWCI 2.78)OA: goldTopics (25)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 (8)

Diep Tran ORCID,Tina Tang ORCID,Anthony Gonzales,Paul Nagy ORCID,Hadi Kharrazi ORCID

Live enrichment

PubMed:39253550 PMC:PMC11382176 OpenAlex:https://openalex.org/W4400763586

NEI NIH HHS

Grant: K23 EY033440

National Institutes of Health

Grant: 5K23EY033440-02

Impact of Social Determinants of Health in Diabetic Retinopathy

Research to Prevent Blindness

National Eye Institute

FWCI

2.78

Citation Percentile

0.9%

Citation Trend

2025

2026

goldLicense: cc-by-nc-nd

journalhttp://www.ophthalmologyscience.org/article/S2666914524001143/pdf

GOLDhttps://doi.org/10.1016/j.xops.2024.100578

publisherhttp://www.ophthalmologyscience.org/article/S2666914524001143/pdf

publisherhttps://api.elsevier.com/content/article/PII:S2666914524001143?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S2666914524001143?httpAccept=text/plain

Fields of Study

Retinal Diseases and TreatmentsRetinal Imaging and AnalysisArtificial Intelligence in HealthcareMedicineComputer Science0301 basic medicine03 medical and health sciences0302 clinical medicine

Keywords

Diabetic retinopathyIdentification (biology)Computer scienceNatural language processingHealth recordsElectronic health recordMedicineArtificial intelligenceDiabetes mellitusHealth careBiologyPolitical sciencePrevalenceClinical Free-text NotesOphthalmologyOriginal ArticleRE1-994

Sustainable Development Goals

SDG 3: 3. Good healthSDG 0: Quality Education

Improving the Identification of Diabetic Retinopathy and Related Conditions in the Electronic Health Record Using Natural Language Processing Methods

FAIR Checklist

Authors (8)

Funding (4 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)