Comparison Between Cox Proportional Hazards and Machine Learning Models for the Prognostication of Recurrence and Survival Following Liver Resection for Hepatocellular Carcinoma.

Journal: Journal of hepato-biliary-pancreatic sciences
Published Date:

Abstract

BACKGROUND: A robust prognostication model after liver resection for hepatocellular carcinoma (HCC) can guide clinical management. We aimed to develop a prognostication model for HCC recurrence and survival following liver resection, comparing between Cox proportional hazards (CPH) and supervised machine learning models.

Authors

  • Hwee-Leong Tan
    Department of Hepatopancreatobiliary and Transplant Surgery, Singapore General Hospital and National Cancer Center, Singapore, Singapore.
  • Claudia Y T Liauw
    Department of Data Science, Singapore General Hospital, Singapore, Singapore.
  • Tse-Lert Chua
    Department of Data Science, Singapore General Hospital, Singapore, Singapore.
  • Amanda Y R Lam
    Department of Data Science, Singapore General Hospital, Singapore, Singapore.
  • Cliburn Chan
    Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.
  • Ye-Xin Koh
    Department of Hepatopancreatobiliary and Transplant Surgery, Singapore General Hospital and National Cancer Center, Singapore, Singapore.
  • Jin-Yao Teo
    Department of Hepatopancreatobiliary and Transplant Surgery, Singapore General Hospital and National Cancer Center, Singapore, Singapore.
  • Peng-Chung Cheow
    Department of Hepatopancreatobiliary and Transplantation Surgery, Singapore General Hospital, Singapore.
  • Alexander Y F Chung
    Department of Hepatopancreatobiliary and Transplantation Surgery, Singapore General Hospital, Singapore.
  • Brian K P Goh
    Department of Hepatopancreatobiliary and Transplant Surgery Singapore General Hospital Singapore and Office of Clinical Sciences, Duke-NUS Graduate Medical School, Singapore.

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