Deep learning and pathomics analyses predict prognosis of high-grade gliomas

Deep learning and pathomics analyses predict prognosis of high-grade gliomas

ObjectiveUtilizing pathomics to analyze high-grade gliomas and provide prognostic insights.MethodsRegions of Interest (ROIs) in tumor areas were identified in whole-slide images (WSI). Tumor patches underwent cropping, white space removal, and normalization. A deep learning model trained on these pa...

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Bibliographic Details
Main Authors: Yuchen Zhu, Yuxi Gong, Weilin Xu, Xingjian Sun, Gefei Jiang, Lei Qiu, Kexin Shi, Mengxing Wu, Yinjiao Fei, Jinling Yuan, Jinyan Luo, Yurong Li, Yuandong Cao, Minhong Pan, Shu Zhou
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Neurology
Subjects:
high-grade gliomas
deep learning
prognostic analysis
pathomics
IDH
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2025.1614678/full
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https://www.frontiersin.org/articles/10.3389/fneur.2025.1614678/full

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