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Morphology-based molecular classification of spinal cord ependymomas using deep neural networks

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cris.customurl 15268
cris.virtual.department High Performance Computing
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cris.virtual.departmentbrowse High Performance Computing
cris.virtual.departmentbrowse High Performance Computing
cris.virtual.departmentbrowse High Performance Computing
cris.virtual.departmentbrowse High Performance Computing
cris.virtual.departmentbrowse High Performance Computing
cris.virtual.departmentbrowse High Performance Computing
cris.virtual.departmentbrowse High Performance Computing
cris.virtual.departmentbrowse High Performance Computing
cris.virtual.departmentbrowse High Performance Computing
cris.virtual.departmentbrowse High Performance Computing
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dc.contributor.author Schumann, Yannis
dc.contributor.author Dottermusch, Matthias
dc.contributor.author Schweizer, Leonille
dc.contributor.author Krech, Maja
dc.contributor.author Lempertz, Tasja
dc.contributor.author Schüller, Ulrich
dc.contributor.author Neumann, Philipp
dc.contributor.author Neumann, Julia E.
dc.date.issued 2024-01-11
dc.description.version HSU-Of
dc.identifier.articlenumber bpa.13239
dc.identifier.doi 10.1111/bpa.13239
dc.identifier.issn 1750-3639
dc.identifier.uri https://openhsu.ub.hsu-hh.de/handle/10.24405/15268
dc.language.iso en
dc.publisher Wiley
dc.relation.journal Brain Pathology
dc.relation.orgunit High Performance Computing
dc.rights.accessRights metadata only access
dc.title Morphology-based molecular classification of spinal cord ependymomas using deep neural networks
dc.type Research article
dspace.entity.type Publication
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