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

Artificial Intelligence–Enabled Software Prototype to Inform Opioid Pharmacovigilance From Electronic Health Records: Development and Usability Study

JMIR AI(2023)10.2196/45000Source: DataRank Database

Artificial Intelligence–Enabled Software Prototype to Inform Opioid Pharmacovigilance From Electronic Health Records: Development and Usability Study is a research paper published in JMIR AI (2023). On theSindex it has a DataRank of 0. It has been cited 13 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access13 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 (2 grants)Impact (FWCI 2.25)OA: goldTopics (26)IDs (PubMed, PMC, OpenAlex)

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 (9)

Syed Arefinul Haque ORCID,Rashedul Hasan ORCID,Richard Jermyn ORCID,Ahmad I. Hussein ORCID,Alex Vega ORCID

Live enrichment

PubMed:37771410 PMC:PMC10538589 OpenAlex:https://openalex.org/W4384694411

Intramural FDA HHS

Grant: FD999999

Intramural NIH HHS

Grant: Z99 LM999999

FWCI

2.25

Citation Percentile

0.9%

Citation Trend

2023

2024

2025

2026

goldLicense: cc-by

journalhttps://jmir.org/api/download?alt_name=ai_v2i1e45000_app1.pdf&filename=d1e14c2762d45b597cc32c121d704443.pdf

publisherhttps://jmir.org/api/download?alt_name=ai_v2i1e45000_app1.pdf&filename=d1e14c2762d45b597cc32c121d704443.pdf

publisherhttps://ai.jmir.org/2023/1/e45000

journalhttps://doi.org/10.2196/45000

repositoryhttps://pubmed.ncbi.nlm.nih.gov/37771410

Fields of Study

Pharmacovigilance and Adverse Drug ReactionsElectronic Health Records SystemsMachine Learning in Healthcare

Keywords

PharmacovigilanceUsabilityComputer scienceArtificial intelligenceMachine learningSoftwarePatient safetyNamed-entity recognitionMedicineHealth careNatural language processingAdverse effectHuman–computer interactionEngineeringPharmacologyDrugNatural LanguageElectronic Health RecordsEhrFood And Drug AdministrationSoftware ApplicationDeep LearningReal World Data