Image-Based Subtype Classification for Glioblastoma Using Deep Learning: Prognostic Significance and Biologic Relevance.

Journal: JCO clinical cancer informatics
Published Date: Jan 1, 2024

Abstract

PURPOSE: To apply deep learning algorithms to histopathology images, construct image-based subtypes independent of known clinical and molecular classifications for glioblastoma, and produce novel insights into molecular and immune characteristics of the glioblastoma tumor microenvironment.

Authors

  • Min Yuan
    College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China.
  • Haolun Ding
    Beijing Wodong Tianjun Information Technology Co., Ltd, Chengdu Branch, Chengdu 610041, Sichuan, China.
  • Bangwei Guo
    School of Data Science, University of Science and Technology of China, Hefei, Anhui, China.
  • Miaomiao Yang
    School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Road, Zhenjiang 212013, Jiangsu, China.
  • Yaning Yang
    Department of Statistics and Finance, University of Science and Technology of China, Hefei, Anhui 230026, China.
  • Xu Steven Xu
    Clinical Pharmacology and Quantitative Science, Genmab Inc., Princeton, NJ, USA. sxu@genmab.com.

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