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

Deep learning–based dose prediction to improve the plan quality of volumetric modulated arc therapy for gynecologic cancers

Medical Physics(2023)10.1002/mp.16735Source: DataRank Database

Deep learning–based dose prediction to improve the plan quality of volumetric modulated arc therapy for gynecologic cancers is a research paper published in Medical Physics (2023). On theSindex it has a DataRank of 0. It has been cited 15 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access15 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 (10 grants)Impact (FWCI 3.69)OA: hybridTopics (50)IDs (PubMed, PMC, OpenAlex)SDGs (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 (19)

Anuja Jhingran ORCID,Tucker Netherton ORCID,Skylar Gay ORCID,Carlos Cárdenas ORCID,Christine Chung ORCID

Live enrichment

PubMed:37706560 PMC:PMC10947338 OpenAlex:https://openalex.org/W4386726659

NCATS NIH HHS

Grant: UL1 TR003167

NCI NIH HHS

Grant: P30 CA016672

NCI NIH HHS

Grant: T32 CA096520

NCATS NIH HHS

Grant: TL1 TR003169

Wellcome Trust

Grant: unidentified

unidentified

National Institutes of Health

Grant: 5TL1TR003169-02

NRSA Training Core

National Institutes of Health

Grant: 3UL1TR003167-02S4

Center for Clinical and Translational Sciences (CCTS)

National Institutes of Health

Grant: 3P30CA016672-41S4

Cancer Center Support (CORE) Grant

Wellcome Trust

Varian Medical Systems

FWCI

3.69

Citation Percentile

0.9%

Citation Trend

2023

2024

2025

2026

hybridLicense: cc-by

journalhttps://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/mp.16735

publisherhttps://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/mp.16735

publisherhttps://aapm.onlinelibrary.wiley.com/doi/pdf/10.1002/mp.16735

journalhttps://doi.org/10.1002/mp.16735

repositoryhttps://pubmed.ncbi.nlm.nih.gov/37706560

Fields of Study

Advanced Radiotherapy TechniquesProstate Cancer Diagnosis and TreatmentEndometrial and Cervical Cancer Treatments02 engineering and technology0202 electrical engineering, electronic engineering, information engineering

MeSH Terms

Deep LearningFemaleHumansNeoplasmsRadiotherapy DosageRadiotherapy Planning, Computer-AssistedRadiotherapy, Intensity-ModulatedOrgans at Risk

Keywords

UsabilityMedicineTest setRadiation oncologistMedical physicsQuality (philosophy)Nuclear medicineSet (abstract data type)Radiation therapyComputer scienceArtificial intelligenceRadiologyQuality assuranceDose PredictionDeep LearningOrgans at RiskMedical SciencesBioinformaticsRadiotherapy Planning610Health and Medical PhysicsBiomedical InformaticsTHERAPEUTIC INTERVENTIONSComputer-AssistedNeoplasmsIntensity-ModulatedMedical SpecialtiesMedicine and Health SciencesHumansRadiotherapyRadiotherapy Planning, Computer-AssistedRadiotherapy Dosage620OncologyFemalePublic HealthRadiotherapy, Intensity-Modulated

Sustainable Development Goals

SDG 0: Good health and well-being