Predicting benefit from PARP inhibitors using deep learning on H&E-stained ovarian cancer slides

Marme, Frederik; Krieghoff-Henning, Eva I.; Kiehl, Lennard; Wies, Christoph; Hauke, Jan; Hahnen, Eric; Harter, Philipp; Schouten, Philip C.; Brodkorb, Tobias; Kayali, Mohamad; Heitz, Florian; Zamagni, Claudio; Gonzalez-Martin, Antonio; Treilleux, Isabelle; Kommoss, Stefan; Prieske, Katharina; Gaiser, Timo; Froehling, Stefan; Ray-Coquard, Isabelle; Pujade-Lauraine, Eric; Brinker, Titus J.

dc.contributor.author	Kommoss, Stefan
dc.date.accessioned	2025-08-01T07:52:40Z
dc.date.available	2025-08-01T07:52:40Z
dc.date.issued	2025
dc.identifier.issn	0959-8049
dc.identifier.uri	http://hdl.handle.net/10900/168664
dc.language.iso	en	en
dc.publisher	London : Elsevier Sci Ltd	de_DE
dc.relation.uri	http://dx.doi.org/10.1016/j.ejca.2024.115199
dc.subject.ddc	610	de_DE
dc.title	Predicting benefit from PARP inhibitors using deep learning on H&E-stained ovarian cancer slides	de_DE
dc.type	Article	de_DE
utue.quellen.id	20250526000000_00021
utue.personen.roh	Marme, Frederik
utue.personen.roh	Krieghoff-Henning, Eva I.
utue.personen.roh	Kiehl, Lennard
utue.personen.roh	Wies, Christoph
utue.personen.roh	Hauke, Jan
utue.personen.roh	Hahnen, Eric
utue.personen.roh	Harter, Philipp
utue.personen.roh	Schouten, Philip C.
utue.personen.roh	Brodkorb, Tobias
utue.personen.roh	Kayali, Mohamad
utue.personen.roh	Heitz, Florian
utue.personen.roh	Zamagni, Claudio
utue.personen.roh	Gonzalez-Martin, Antonio
utue.personen.roh	Treilleux, Isabelle
utue.personen.roh	Kommoss, Stefan
utue.personen.roh	Prieske, Katharina
utue.personen.roh	Gaiser, Timo
utue.personen.roh	Froehling, Stefan
utue.personen.roh	Ray-Coquard, Isabelle
utue.personen.roh	Pujade-Lauraine, Eric
utue.personen.roh	Brinker, Titus J.
dcterms.isPartOf.ZSTitelID	European Journal of Cancer	de_DE
dcterms.isPartOf.ZS-Issue	Article 115199	de_DE
dcterms.isPartOf.ZS-Volume	216	de_DE
utue.fakultaet	04 Medizinische Fakultät