Multiparametric Oncologic Hybrid Imaging: Machine Learning Challenges and Opportunities

dc.contributor.author	Hepp, Tobias
dc.contributor.author	Küstner, Thomas
dc.contributor.author	Seith, Ferdinand Frederic
dc.date.accessioned	2024-05-06T08:18:58Z
dc.date.available	2024-05-06T08:18:58Z
dc.date.issued	2023
dc.identifier.issn	0029-5566
dc.identifier.uri	http://hdl.handle.net/10900/153132
dc.language.iso	en	de_DE
dc.publisher	Stuttgart : Georg Thieme Verlag KG	de_DE
dc.relation.uri	http://dx.doi.org/10.1055/a-2157-6670	de_DE
dc.subject.ddc	610	de_DE
dc.title	Multiparametric Oncologic Hybrid Imaging: Machine Learning Challenges and Opportunities	de_DE
dc.type	Article	de_DE
utue.quellen.id	20240124000000_00985
utue.publikation.seiten	306-313	de_DE
utue.personen.roh	Kuestner, Thomas
utue.personen.roh	Hepp, Tobias
utue.personen.roh	Seith, Ferdinand
dcterms.isPartOf.ZSTitelID	Nuklearmedizin - Nuclear Medicine	de_DE
dcterms.isPartOf.ZS-Issue	5	de_DE
dcterms.isPartOf.ZS-Volume	62	de_DE
utue.fakultaet	04 Medizinische Fakultät	de_DE

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