Application of preoperative artificial neural network based on blood biomarkers and clinicopathological parameters for predicting long-term survival of patients with gastric cancer.

Journal: World journal of gastroenterology
Published Date: Nov 21, 2019

Abstract

BACKGROUND: Because of the powerful abilities of self-learning and handling complex biological information, artificial neural network (ANN) models have been widely applied to disease diagnosis, imaging analysis, and prognosis prediction. However, there has been no trained preoperative ANN (preope-ANN) model to preoperatively predict the prognosis of patients with gastric cancer (GC).

Authors

  • Si-Jin Que
    Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China.
  • Qi-Yue Chen
    Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China.
  • Qing-Zhong
    Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China.
  • Zhi-Yu Liu
    Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China.
  • Jia-Bin Wang
    Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China.
  • Jian-Xian Lin
    Department of Gastric Surgery, Fujian Medical University Union Hospital, No. 29, Xinquan Road, Fuzhou, 350001, Fujian Province, China. linjian379@163.com.
  • Jun Lu
    School of Acupuncture-moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing 100029, China.
  • Long-Long Cao
    Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China.
  • Mi Lin
    Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China.
  • Ru-Hong Tu
    Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China.
  • Ze-Ning Huang
    Department of Gastric Surgery, Fujian Medical University Union Hospital, No. 29, Xinquan Road, Fuzhou, 350001, Fujian Province, China.
  • Ju-Li Lin
    Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China.
  • Hua-Long Zheng
    Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China.
  • Ping Li
    Department of Gastroenterology, Beijing Ditan Hospital, Capital Medical University, Beijing, China.
  • Chao-Hui Zheng
    Department of Gastric Surgery, Fujian Medical University Union Hospital, No. 29, Xinquan Road, Fuzhou, 350001, Fujian Province, China.
  • Chang-Ming Huang
    Department of Gastric Surgery, Fujian Medical University Union Hospital, No. 29, Xinquan Road, Fuzhou, 350001, Fujian Province, China. hcmlr2002@163.com.
  • Jian-Wei Xie
    Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China.

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