Nonlinear association between visceral fat metabolism score and heart failure: insights from LightGBM modeling and SHAP-Driven feature interpretation in NHANES.

Journal: BMC medical informatics and decision making
Published Date: Jul 1, 2025

Abstract

OBJECTIVE: Using 2005-2018 NHANES data, this study examined the association between the visceral fat metabolism score (METS-VF) and heart failure (HF) prevalence in U.S. adults, leveraging machine learning (LightGBM/XGBoost) and SHAP for classfication performance evaluation and feature interpretation.

Authors

  • Ningyi Cheng
    Department of Cardiovascular Surgery, Fujian Medical University Union Hospital, Fuzhou, China.
  • Yukun Chen
    Department of Biomedical Informatics, Vanderbilt University, School of Medicine, Nashville, TN, USA.
  • Lei Jin
    Department of Chemistry, University of Connecticut, Storrs, Connecticut 06269, United States.
  • Liangwan Chen
    Department of Cardiovascular Surgery, Union Hospital, Fujian Medical University, No. 6, Xuefu South Road, Shangjie Town, Minhou County, 350108, Fuzhou, China. fjxhlwc@163.com.

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