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Three-Dimensional Deep Learning Normal Tissue Complication Probability Model to Predict Late Xerostomia in Patients With Head and Neck Cancer

International Journal of Radiation Oncology*Biology*Physics(2024)10.1016/j.ijrobp.2024.07.2334Source: DataRank Database

Three-Dimensional Deep Learning Normal Tissue Complication Probability Model to Predict Late Xerostomia in Patients With Head and Neck Cancer is a research paper published in International Journal of Radiation Oncology*Biology*Physics (2024). On theSindex it has a DataRank of 0. It has been cited 10 times.

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Open Access10 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (18 grants)Impact (FWCI 3.99)OA: hybridTopics (44)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)

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Authors (10)

Suzanne P.M. de Vette ORCID,Hendrike Neh,Nanna M. Sijtsema ORCID,Roel J.H.M. Steenbakkers ORCID,Amy C. Moreno ORCID

Live enrichment

PubMed:39147208 PMC:PMC11646177 OpenAlex:https://openalex.org/W4401539037

Nihon Superior

Grant: R01CA225190

Nihon Superior

Grant: NSF-1933369

KWF Kankerbestrijding

Grant: KWF-13529

NIHR BioResource

Grant: R01CA258827

NIHR BioResource

Grant: R01CA214825

NIHR BioResource

Grant: R01CA218148

NIHR BioResource

Grant: R01DE028290

NIHR BioResource

Grant: R25EB025787

NIHR BioResource

Grant: 1R21DE031082-01

NIHR BioResource

Grant: 1K01DE030524-01A1

NIHR BioResource

Grant: R21DE031082

NIDCR NIH HHS

Grant: K01 DE030524

NCI NIH HHS

Grant: P30 CA016672

NIDCR NIH HHS

Grant: U01 DE032168

ZonMw

Grant: 09150162010173

Dutch Arthritis Society

ZonMw

Kansas NSF EPSCoR

FWCI

3.99

Citation Percentile

0.9%

Citation Trend

2025

2026

hybridLicense: cc-by

journalhttp://www.redjournal.org/article/S0360301624031729/pdf

publisherhttp://www.redjournal.org/article/S0360301624031729/pdf

publisherhttps://api.elsevier.com/content/article/PII:S0360301624031729?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S0360301624031729?httpAccept=text/plain

journalhttps://doi.org/10.1016/j.ijrobp.2024.07.2334

Fields of Study

Head and Neck Cancer StudiesSalivary Gland Disorders and FunctionsRadiomics and Machine Learning in Medical ImagingHumansXerostomiaDeep LearningHead and Neck NeoplasmsFemaleMaleMiddle AgedOrgans at RiskAgedSalivary GlandsProbabilityAdultTomography, X-Ray ComputedRadiotherapy DosageRadiation InjuriesAged, 80 and over

MeSH Terms

Deep LearningAdultAgedAged, 80 and overFemaleHead and Neck NeoplasmsHumansMaleMiddle AgedProbabilityRadiation InjuriesRadiotherapy DosageSalivary GlandsTomography, X-Ray ComputedXerostomiaOrgans at Risk

Keywords

Head and neck cancerComplicationHead and neckMedicineCancerHead (geology)SurgeryInternal medicineGeology