Integrated clinicopathological-radiomic-blood model for glioma survival prediction via machine learning: a multicenter cohort study.

Journal: Neurosurgical review
Published Date: Jul 12, 2025

Abstract

BACKGROUND: Glioma is characterized by a poor prognosis and limited possibilities for treatment. Previous studies have developed prediction models for glioma using genetic, clinical, pathological, imaging and other aspects; however, few studies have combined these data. The current study is intended to fully utilize medical data from the routine practice of glioma care and develop a model with the assistance of machine learning.

Authors

  • Zhihao Wang
    School of Information Science and Engineering, Shandong Normal University, Jinan, Shandong, China; Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology, Jinan, Shandong, China.
  • Tao Chang
    College of Computer, National University of Defense Technology, Kaifu District, Changsha 410073, China. Electronic address: changtao15@nudt.edu.cn.
  • Jing Yang
    Beijing Novartis Pharma Co. Ltd., Beijing, China.
  • Chaodong Xiang
    7 T Magnetic Resonance Translational Medicine Research Center, Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
  • Xianqi Wang
    Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
  • Pinzhen Chen
    Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
  • Yunhui Zeng
    Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China.
  • Lanqin Deng
    Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China.
  • Wenhao Li
    Flight Control Research Institute, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China.
  • Yuhang Ou
    Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China.
  • Siliang Chen
    Department of Neurosurgery, West China Hospital, Sichuan University, 37 Guoxue Avenue, Chengdu, 610041, People's Republic of China.
  • Hao Ren
    Department of Rheumatology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China. Electronic address: renhao67@aliyun.com.
  • Yuan Yang
    The Ministry of Education Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Northwestern Polytechnical University, No. 127, Youyi Road (West), Xi'an 710072, China.
  • Xiaofei Hu
    Department of Radiology, Southwest Hospital, Third Military Medical University (Army Military Medical University), Chongqing, China.
  • Qing Mao
    Department of Neurosurgery, West China Hospital of Sichuan University, Chengdu, China.
  • Wei Chen
    Department of Urology, Zigong Fourth People's Hospital, Sichuan, China.
  • Yanhui Liu
    Department of Neurosurgery, West China Hospital of Sichuan University, Chengdu, China.

Keywords

External Resources

Popular Topics
Recent Journals