Conventional and machine learning-based risk scores for patients with early-stage hepatocellular carcinoma.

Journal: Clinical and molecular hepatology
Published Date: Apr 11, 2024

Abstract

BACKGROUND/AIMS: The performance of machine learning (ML) in predicting the outcomes of patients with hepatocellular carcinoma (HCC) remains uncertain. We aimed to develop risk scores using conventional methods and ML to categorize early-stage HCC patients into distinct prognostic groups.

Authors

  • Chun-Ting Ho
    Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.
  • Elise Chia-Hui Tan
    Department of Health Service Administration, College of Public Health, China Medical University, Taichung, Taiwan.
  • Pei-Chang Lee
    Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.
  • Chi-Jen Chu
    Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.
  • Yi-Hsiang Huang
    Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan. yhhuang@vghtpe.gov.tw.
  • Teh-Ia Huo
    Division of Basic Research, Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan.
  • Yu-Hui Su
    Department of Accounting, Soochow University, Taipei, Taiwan.
  • Ming-Chih Hou
    Endoscopy Center for Diagnosis and Treatment, Taipei Veterans General Hospital, Taipei, Taiwan.
  • Jaw-Ching Wu
    Institute of Clinical Medicine, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
  • Chien-Wei Su
    Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.

Keywords

External Resources

Popular Topics
Recent Journals