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Article

Deep learning links localized digital pathology phenotypes with transcriptional subtype and patient outcome in glioblastoma.

GigaScience - 2 Jan 2024

Roetzer-Pejrimovsky Thomas, Nenning Karl-Heinz, Kiesel Barbara, Klughammer Johanna, Rajchl Martin, Baumann Bernhard, Langs Georg, Woehrer Adelheid

Abstract excerpt

BACKGROUND: Deep learning has revolutionized medical image analysis in cancer pathology, where it had a substantial clinical impact by supporting the diagnosis and prognostic rating of cancer. Among the first available digital resources in the field of brain cancer is glioblastoma, the most common and fatal brain cancer. At the histologic level, glioblastoma is characterized by abundant phenotypic variability...

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Share to AI in cancer detection
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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Source

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Identifiers

PMID: 39185700
DOI: 10.1093/gigascience/giae057
PMCID: PMC11345537

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