Machine learning-driven risk assessment of coronary heart disease: Analysis of NHANES data from 1999 to 2018.

Journal: Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences
PMID: 39788507

Abstract

OBJECTIVES: The high incidence of coronary artery heart disease (CHD) poses a significant burden and challenge to public health systems globally. Effective prevention and early diagnosis of CHD have become key strategies to alleviate this burden. This study aims to explore the application of advanced machine learning techniques to enhance the accuracy of early screening and risk assessment for CHD.

Authors

  • Jin Lu
    Computer Science & Engineering Department at the University of Connecticut.
  • Haochang Hu
    Department of Cardiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009.
  • Jiaming Xiu
    Department of Cardiology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan Fujian 364000.
  • Yanfang Yang
    Department of Cardiology, Provincial Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou 350001.
  • Qifeng Zhu
    Department of Cardiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009.
  • Hanyi Dai
    Department of Cardiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009.
  • Xianbao Liu
    Department of Cardiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009.
  • Jian'an Wang
    Department of Cardiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009. wangjianan111@zju.edu.cn.

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