Machine learning prediction model with shap interpretation for chronic bronchitis risk assessment based on heavy metal exposure: a nationally representative study.

Journal: BMC pulmonary medicine
Published Date:

Abstract

BACKGROUND: Chronic bronchitis (CB), as a core precursor of Chronic Obstructive Pulmonary Disease (COPD), is crucial for global disease burden prevention and control. Although the association between heavy metal exposure and respiratory damage has been preliminarily demonstrated, traditional linear models are difficult to resolve the nonlinear interactions and dose-response heterogeneity. The aim of this study was to construct the first heavy metal exposure-chronic bronchitis risk prediction model by integrating exposureomics data through machine learning (ML).

Authors

  • Tiansheng Xia
    Department of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, 246 Xuefu Road, Nangang District, Harbin, 150001, China.
  • Kaiyu Han
    Department of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, 246 Xuefu Road, Nangang District, Harbin, 150001, China. hankaiyu2002@163.com.