A deep-learning workflow to predict upper tract urothelial carcinoma protein-based subtypes from H&E slides supporting the prioritization of patients for molecular testing

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dc.contributor.author Bahlinger, Veronika
dc.date.accessioned 2024-07-02T06:54:33Z
dc.date.available 2024-07-02T06:54:33Z
dc.date.issued 2024
dc.identifier.issn 2056-4538
dc.identifier.uri http://hdl.handle.net/10900/154623
dc.language.iso en de_DE
dc.publisher Hoboken : Wiley de_DE
dc.relation.uri http://dx.doi.org/10.1002/2056-4538.12369 de_DE
dc.subject.ddc 610 de_DE
dc.title A deep-learning workflow to predict upper tract urothelial carcinoma protein-based subtypes from H&E slides supporting the prioritization of patients for molecular testing de_DE
dc.type Article de_DE
utue.quellen.id 20240422000000_00327
utue.personen.roh Angeloni, Miriam
utue.personen.roh van Doeveren, Thomas
utue.personen.roh Lindner, Sebastian
utue.personen.roh Volland, Patrick
utue.personen.roh Schmelmer, Jorina
utue.personen.roh Foersch, Sebastian
utue.personen.roh Matek, Christian
utue.personen.roh Stoehr, Robert
utue.personen.roh Geppert, Carol, I
utue.personen.roh Heers, Hendrik
utue.personen.roh Wach, Sven
utue.personen.roh Taubert, Helge
utue.personen.roh Sikic, Danijel
utue.personen.roh Wullich, Bernd
utue.personen.roh van Leenders, Geert J. L. H.
utue.personen.roh Zaburdaev, Vasily
utue.personen.roh Eckstein, Markus
utue.personen.roh Hartmann, Arndt
utue.personen.roh Boormans, Joost L.
utue.personen.roh Ferrazzi, Fulvia
utue.personen.roh Bahlinger, Veronika
dcterms.isPartOf.ZSTitelID Journal of Pathology Clinical Research de_DE
dcterms.isPartOf.ZS-Issue Article e12369 de_DE
dcterms.isPartOf.ZS-Volume 10 (2) de_DE
utue.fakultaet 04 Medizinische Fakultät de_DE


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