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dc.contributor.authorKechagioglou, Penny
dc.date.accessioned2023-08-17T10:29:24Z
dc.date.available2023-08-17T10:29:24Z
dc.date.issued2023-05-01
dc.identifier.citationSemin Oncol Nurs . 2023 Jun;39(3):151430en_US
dc.identifier.eissn1878-3449
dc.identifier.doi10.1016/j.soncn.2023.151430
dc.identifier.pmid37137769
dc.identifier.urihttp://hdl.handle.net/20.500.14200/1715
dc.description.abstractObjectives: There is a vast amount of real-world data collected daily in oncology through diagnostic, therapeutic, and patient-reported outcome measures. The challenge arises with linking data together to create structured and meaningful databases, which are representative of the general population, free of bias, and of good quality to be able to draw meaningful conclusions. Real-world data that are linked together within trusted cancer research environments could represent the next generation of big data strategy in cancer.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rightsCopyright © 2023 Elsevier Inc. All rights reserved.
dc.subjectOncology. Pathology.en_US
dc.subjectHealth services. Managementen_US
dc.titleBig Data in Oncology: The Electronic Patient Record Transformation Program.en_US
dc.typeArticle
dc.source.journaltitleSeminars in Oncology Nursing
dc.source.volume39
dc.source.issue3
dc.source.beginpage151430
dc.source.endpage
dc.source.countryUnited States
rioxxterms.versionNAen_US
dc.contributor.trustauthorKechagioglou, Penny
dc.contributor.departmentMedicineen_US
dc.contributor.roleMedical and Dentalen_US
oa.grant.openaccessnaen_US


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