Predicting Resistance and Survival of HCC Patients Post-HAIC: Based on Shapley Additive exPlanations and Machine Learning.

Journal: Journal of hepatocellular carcinoma
Published Date: May 31, 2025

Abstract

PURPOSE: To establish prediction models using Shapley Additive exPlanations (SHAP) and multiple machine learning (ML) algorithms to identify clinical features influencing hepatic arterial infusion chemotherapy (HAIC) resistance and survival in patients with hepatocellular carcinoma (HCC).

Authors

  • Fan Yao
    Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
  • Jianliang Miao
    First Affiliated Hospital of Dalian Medical University, Dalian Medical University, Dalian, China.
  • Bing Quan
    Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
  • Jinghuan Li
    Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
  • Bei Tang
    Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
  • Shenxin Lu
    Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
  • Xin Yin
    3School of Software & Microelectronics, Peking University, Beijing, 102600 China.

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