NecroGlobalGCN: Integrating micronecrosis information in HCC prognosis prediction via graph convolutional neural networks.

Journal: Computer methods and programs in biomedicine
PMID: 39357091

Abstract

BACKGROUND AND OBJECTIVE: Hepatocellular carcinoma (HCC) ranks fourth in cancer mortality, underscoring the importance of accurate prognostic predictions to improve postoperative survival rates in patients. Although micronecrosis has been shown to have high prognostic value in HCC, its application in clinical prognosis prediction requires specialized knowledge and complex calculations, which poses challenges for clinicians. It would be of interest to develop a model to help clinicians make full use of micronecrosis to assess patient survival.

Authors

  • Boyang Deng
  • Yu Tian
    Key Laboratory of Development and Maternal and Child Diseases of Sichuan Province, Department of Pediatrics, Sichuan University, Chengdu, China.
  • Qi Zhang
    Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Yangyang Wang
  • Zhenxin Chai
    Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, No. 38 Zheda Road, Hangzhou 310027, China.
  • Qiancheng Ye
  • Shang Yao
    Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, No. 38 Zheda Road, Hangzhou 310027, China.
  • Tingbo Liang
    Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital, State Key Laboratory of Modern Optical Instrumentation, Zhejiang University School of Medicine, Hangzhou 310003, China.
  • Jingsong Li
    Research Center for Healthcare Data Science, Zhejiang Lab, Hangzhou, China.

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