Prognostic stratification of glioblastoma patients by unsupervised clustering of morphology patterns on whole slide images furthering our disease understanding

• Published in: Frontiers in neuroscience Vol. 18; p. 1304191
• Main Authors: Baheti, Bhakti, Innani, Shubham, Nasrallah, MacLean, Bakas, Spyridon
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 20.05.2024
• Subjects: clustering; computational pathology; glioblastoma; morphology; Neuroscience; stratification; survival; clustering; computational pathology; glioblastoma; morphology; stratification; survival

Glioblastoma (GBM) is a highly aggressive malignant tumor of the central nervous system that displays varying molecular and morphological profiles, leading to challenging prognostic assessments. Stratifying GBM patients according to overall survival (OS) from H&E-stained whole slide images (WSI)...