Big Data in Oncology: The Electronic Patient Record Transformation Program.
dc.contributor.author | Kechagioglou, Penny | |
dc.date.accessioned | 2023-08-17T10:29:24Z | |
dc.date.available | 2023-08-17T10:29:24Z | |
dc.date.issued | 2023-05-01 | |
dc.identifier.citation | Semin Oncol Nurs . 2023 Jun;39(3):151430 | en_US |
dc.identifier.eissn | 1878-3449 | |
dc.identifier.doi | 10.1016/j.soncn.2023.151430 | |
dc.identifier.pmid | 37137769 | |
dc.identifier.uri | http://hdl.handle.net/20.500.14200/1715 | |
dc.description.abstract | Objectives: 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.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | Copyright © 2023 Elsevier Inc. All rights reserved. | |
dc.subject | Oncology. Pathology. | en_US |
dc.subject | Health services. Management | en_US |
dc.title | Big Data in Oncology: The Electronic Patient Record Transformation Program. | en_US |
dc.type | Article | |
dc.source.journaltitle | Seminars in Oncology Nursing | |
dc.source.volume | 39 | |
dc.source.issue | 3 | |
dc.source.beginpage | 151430 | |
dc.source.endpage | ||
dc.source.country | United States | |
rioxxterms.version | NA | en_US |
dc.contributor.trustauthor | Kechagioglou, Penny | |
dc.contributor.department | Medicine | en_US |
dc.contributor.role | Medical and Dental | en_US |
oa.grant.openaccess | na | en_US |