Deep-Learning-Based Model for the Prediction of Cancer-Specific Survival in Patients with Spinal Chordoma.

Journal: World neurosurgery
PMID: 37586553

Abstract

OBJECTIVE: Spinal chordomas are locally aggressive and frequently recurrent tumors with a poor prognosis. Previous studies focused on a Cox regression model to predict the survival of patients with spinal chordoma. We aimed to develop a more effective model based on deep learning for prognosis prediction in spinal chordoma.

Authors

  • Debin Cheng
    Department of Orthopaedics, Xijing Hospital Affiliated to The Fourth Military Medical University, Xi'an, Shanxi, China.
  • Dong Liu
    Department of Gastrointestinal Surgery, The Third Hospital of Hebei Medical University, Shijiazhuang, China.
  • Xian Li
    Laboratory of Fruit Quality Biology, Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology, The State Agriculture Ministry Laboratory of Horticultural Plant Growth, Development and Quality Improvement, Zhejiang University, Hangzhou 310058, China.
  • Zhao Zhang
  • Zhenzhou Mi
    Department of Orthopaedics, Xijing Hospital Affiliated to The Fourth Military Medical University, Xi'an, Shanxi, China.
  • Weidong Tao
    Department of Orthopaedics, Xijing Hospital Affiliated to The Fourth Military Medical University, Xi'an, Shanxi, China.
  • Jun Fu
    Department of Neurosurgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China.
  • Hongbin Fan

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