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

A Multi-Institutional Natural Language Processing Pipeline to Extract Performance Status From Electronic Health Records

Cancer Control(2024)10.1177/10732748241279518Source: DataRank Database

A Multi-Institutional Natural Language Processing Pipeline to Extract Performance Status From Electronic Health Records is a research paper published in Cancer Control (2024). On theSindex it has a DataRank of 0. It has been cited 3 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access3 citations

Download PDF

Cite:

Linked data & code

gen 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 (7 grants)Impact (FWCI 0.70)OA: goldTopics (69)IDs (PubMed, PMC, OpenAlex)Annotations (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)

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)

Yvonne H. Sada ORCID,Sara Nowakowski ORCID,Danielle Guffey ORCID,Huili Zhu ORCID,Sudha Yarlagadda ORCID

Live enrichment

PubMed:39222957 PMC:PMC11369884 OpenAlex:https://openalex.org/W4402205922

Artificial Intelligence/Machine Learning Consortium to Advance Health Equity And Reseacher Diversity

Grant: OD032581-01S1

Baylor College of Medicine

Grant: CIN 13-413

National Institutes of Health

Grant: #:1K25HL152006-01

U.S. Department of Veterans Affairs

Grant: IK2 CX001981

NIH HHS

Grant: OT2 OD032581

NHLBI NIH HHS

Grant: K25 HL152006

National Institutes of Health

Grant: 1K25HL152006-01

Using Large Electronic Health Records and Advanced Analytics to Develop Predictive Frailty Trajectories in Patients with Heart Failure

FWCI

0.70

Citation Percentile

0.8%

Citation Trend

2025

goldLicense: cc-by-nc

journalhttps://doi.org/10.1177/10732748241279518

GOLDhttps://doi.org/10.1177/10732748241279518

publisherhttps://doi.org/10.1177/10732748241279518

publisherhttps://journals.sagepub.com/doi/pdf/10.1177/10732748241279518

publisherhttps://journals.sagepub.com/doi/full-xml/10.1177/10732748241279518

Fields of Study

Machine Learning in HealthcareElectronic Health Records SystemsData Quality and ManagementMedicineComputer Science03 medical and health sciences0302 clinical medicineHumansNatural Language ProcessingElectronic Health RecordsMaleFemaleLung NeoplasmsCarcinoma, Non-Small-Cell LungMiddle AgedNeoplasms

MeSH Terms

Carcinoma, Non-Small-Cell LungFemaleHumansLung NeoplasmsMaleMiddle AgedNatural Language ProcessingNeoplasmsElectronic Health Records

Keywords

MedicinePipeline (software)DocumentationElectronic health recordLogistic regressionArtificial intelligenceMetric (unit)Medical recordTest (biology)Electronic medical recordCohortStage (stratigraphy)Natural language processingMachine learningHealth careFamily medicineInternal medicineComputer scienceOperations managementNon small cell lung cancerPerformance StatusAmerican Society Of Clinical OncologyEastern Cooperative Oncology GroupQuality MetricMaleMedical SciencesLung Neoplasms610DiseasesCarcinoma, Non-Small-Cell LungNeoplasmsMedical SpecialtiesMedicine and Health SciencesHumansElectronic Health RecordsNon-Small-Cell LungRC254-282CarcinomaNeoplasms. Tumors. Oncology. Including cancer and carcinogensHealth Information TechnologyMiddle AgedOncologyFemaleResearch Article

A Multi-Institutional Natural Language Processing Pipeline to Extract Performance Status From Electronic Health Records

FAIR Checklist

Authors (8)

Funding (7 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)