An interpretable machine learning model for predicting depression in middle-aged and elderly cancer patients in China: a study based on the CHARLS cohort.

Journal: BMC psychiatry
Published Date: Jul 1, 2025

Abstract

BACKGROUND: Depression is very common in middle-aged and elderly cancer patients, which will seriously damage the quality of life and treatment effect of patients. This study aims to use machine learning methods to develop a predictive model to identify depression risk. However, since the traditional machine learning models have 'black box nature', Shapley Additive exPlanation is used to determine the key risk factors.

Authors

  • Yue Xiao
    School of Mechanical Engineering, Nanchang Institute of Technology, Nanchang, Jiangxi 330099, China.
  • Zejin Zhao
    Department of Hepatobiliary Surgery, The Affiliated Hospital of Chengde Medical University, Chengde, 067000, Hebei Province, China.
  • Chen-Guang Su
    Department of Hepatobiliary Surgery, The Affiliated Hospital of Chengde Medical University, Chengde, 067000, Hebei Province, China.
  • Jian Li
    Fujian Key Laboratory of Traditional Chinese Veterinary Medicine and Animal Health, College of Animal Science, Fujian Agriculture and Forestry University, Fuzhou, China.
  • Jinlong Liu
    Institute of Advanced Research, Infervision Medical Technology Co., Ltd, Beijing, China.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals