Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/29626
DC FieldValueLanguage
dc.contributor.authorCharalambous, Andreas-
dc.contributor.authorDodlek, Nikolina-
dc.date.accessioned2023-07-04T12:50:49Z-
dc.date.available2023-07-04T12:50:49Z-
dc.date.issued2023-06-
dc.identifier.citationSeminars in oncology nursing, 2023, vol. 39, no. 3, pp. 1-4en_US
dc.identifier.issn07492081-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/29626-
dc.description.abstractThe rapid advances in artificial intelligence (AI), big data, and machine learning (ML) technologies hold promise for personalized, equitable cancer care and improved health outcomes within the context of cancer and beyond. Furthermore, integrating these technologies into cancer research has been effective in addressing many of the challenges for cancer control and cure. This can be achieved through the insights generated from massive amounts of data, in ways that can help inform decisions, interventions, and precision cancer care. AI, big data, and ML technologies offer, either in isolation or in combination, unconventional pathways that facilitate the better understanding and management of cancer and its impact on the person. The value of AI, big data, and ML technologies has been acknowledged and integrated within the Cancer Moonshot program in the U.S. and the EU Beating Cancer Plan in Europe.en_US
dc.formatPdfen_US
dc.language.isoenen_US
dc.relation.ispartofSeminars in oncology nursingen_US
dc.rightsCopyright © Elsevier B.V.en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.subjectArtificial intelligenceen_US
dc.subjectBig dataen_US
dc.subjectCancer careen_US
dc.subjectDiagnosticsen_US
dc.subjectMachine learningen_US
dc.subjectTelemonitoringen_US
dc.titleBig Data, Machine Learning, and Artificial Intelligence to Advance Cancer Care: Opportunities and Challengesen_US
dc.typeArticleen_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationUniversity of Turkuen_US
dc.collaborationClinical Medical Center Osijeken_US
dc.subject.categoryMEDICAL AND HEALTH SCIENCESen_US
dc.journalsHybrid Open Accessen_US
dc.countryCyprusen_US
dc.countryCroatiaen_US
dc.countryFinlanden_US
dc.subject.fieldMedical and Health Sciencesen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1016/j.soncn.2023.151429en_US
dc.identifier.pmid37085405-
dc.identifier.scopus2-s2.0-85153327213-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85153327213-
dc.relation.issue3en_US
dc.relation.volume39en_US
cut.common.academicyear2022-2023en_US
dc.identifier.spage1en_US
dc.identifier.epage4en_US
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
item.openairetypearticle-
crisitem.author.deptDepartment of Nursing-
crisitem.author.facultyFaculty of Health Sciences-
crisitem.author.orcid0000-0003-4050-031X-
crisitem.author.parentorgFaculty of Health Sciences-
Appears in Collections:Άρθρα/Articles
CORE Recommender
Show simple item record

SCOPUSTM   
Citations 50

1
checked on Feb 2, 2024

Page view(s) 50

202
Last Week
3
Last month
32
checked on Mar 14, 2025

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons