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Artificial intelligence: Deep learning in oncological radiomics and challenges of interpretability and data harmonization

dc.affiliationUniwersytet Warszawski
dc.contributor.authorVermet, Franck
dc.contributor.authorKagadis, George C.
dc.contributor.authorPapadimitroulas, Panagiotis
dc.contributor.authorPlachouris, Dimitris
dc.contributor.authorGaubert, Laurent
dc.contributor.authorHatt, Mathieu
dc.contributor.authorBrocki, Lennart
dc.contributor.authorMarchadour, Wistan
dc.contributor.authorVisvikis, Dimitris
dc.contributor.authorEleftheriadis, Vasilis
dc.contributor.authorChung, Neo Christopher
dc.date.accessioned2024-01-24T16:56:30Z
dc.date.available2024-01-24T16:56:30Z
dc.date.issued2021
dc.description.financePublikacja bezkosztowa
dc.description.volume83
dc.identifier.doi10.1016/J.EJMP.2021.03.009
dc.identifier.issn1120-1797
dc.identifier.urihttps://repozytorium.uw.edu.pl//handle/item/101155
dc.identifier.weblinkhttps://api.elsevier.com/content/article/PII:S1120179721001253?httpAccept=text/xml
dc.languageeng
dc.pbn.affiliationcomputer and information sciences
dc.relation.ispartofPhysica Medica
dc.relation.pages108-121
dc.rightsClosedAccess
dc.sciencecloudnosend
dc.titleArtificial intelligence: Deep learning in oncological radiomics and challenges of interpretability and data harmonization
dc.typeJournalArticle
dspace.entity.typePublication