Identification of prognostic signatures in remnant gastric cancer through an interpretable risk model based on machine learning: a multicenter cohort study.

Journal: BMC cancer
PMID:

Abstract

OBJECTIVE: The purpose of this study was to develop an individual survival prediction model based on multiple machine learning (ML) algorithms to predict survival probability for remnant gastric cancer (RGC).

Authors

  • Zhouwei Zhan
    Department of Medical Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No. 420 Fuma Road, Fuzhou, Fujian, 350014, People's Republic of China.
  • Bijuan Chen
    Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, 350014, People's Republic of China.
  • Hui Cheng
    School of Medicine, Sun Yat-sen University, Guangzhou, China.
  • Shaohua Xu
    College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, Shandong Province, China.
  • Chunping Huang
    Department of Pharmacy, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, 350014, People's Republic of China.
  • Sijing Zhou
    Department of Medical Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No. 420 Fuma Road, Fuzhou, Fujian, 350014, People's Republic of China.
  • Haiting Chen
    School of Basic Medical Sciences of Fujian Medical University, Fuzhou, Fujian, 350004, People's Republic of China.
  • Xuanping Lin
    School of Basic Medical Sciences of Fujian Medical University, Fuzhou, Fujian, 350004, People's Republic of China.
  • Ruyu Lin
    School of Basic Medical Sciences of Fujian Medical University, Fuzhou, Fujian, 350004, People's Republic of China.
  • Wanting Huang
    School of Chemistry, Sun Yat-sen University, Guangzhou 510275, China.
  • Xiaohuan Ma
    School of Basic Medical Sciences of Fujian Medical University, Fuzhou, Fujian, 350004, People's Republic of China.
  • Yu Fu
    Molecular Diagnosis and Treatment Center for Infectious Diseases Dermatology Hospital Southern Medical University Guangzhou China.
  • Zhipeng Chen
    Jiangsu Key Laboratory of Chinese Medicine Processing, Engineering Center of State Ministry of Education for Standardization of Chinese Medicine Processing, Nanjing University of Chinese Medicine, Nanjing 210023, China; Pharmacy College of Nanjing University of Chinese Medicine, Nanjing 210023, China. Electronic address: cpuczp2000@hotmail.com.
  • Hanchen Zheng
    Department of Medical Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No. 420 Fuma Road, Fuzhou, Fujian, 350014, People's Republic of China.
  • Songchang Shi
    Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Zengqing Guo
    Department of Medical Oncology, Fujian Cancer Hospital, Fujian Medical University Cancer Hospital, Fuzhou, Fujian, 350014, China. Electronic address: gzq_005@126.com.
  • Lihui Zhang
    College of Civil Engineering and Architecture, Zhejiang University, 866, Yuhangtang Road, Hangzhou, 310058, China.