Machine learning-based coronary artery calcium score predicted from clinical variables as a prognostic indicator in patients referred for invasive coronary angiography.

Journal: European radiology
Published Date: Feb 10, 2024

Abstract

OBJECTIVES: Utilising readily available clinical variables, we aimed to develop and validate a novel machine learning (ML) model to predict severe coronary calcification, and further assessed its prognostic significance.

Authors

  • Wen Jian
    Center for Coronary Artery Disease, Beijing Anzhen Hospital of Capital Medical University, Beijing, China.
  • Zhujun Dong
    Beijing Anzhen Hospital of Capital Medical University and Beijing Institute of Heart Lung and Blood Vessel Diseases, Beijing, China.
  • Xueqian Shen
    Center for Coronary Artery Disease, Beijing Anzhen Hospital of Capital Medical University, Beijing, China.
  • Ze Zheng
    Center for Coronary Artery Disease, Beijing Anzhen Hospital of Capital Medical University, Beijing, China.
  • Zheng Wu
  • Yuchen Shi
    Center for Coronary Artery Disease, Beijing Anzhen Hospital of Capital Medical University, Beijing, China.
  • Yingchun Han
    Beijing Anzhen Hospital of Capital Medical University and Beijing Institute of Heart Lung and Blood Vessel Diseases, Beijing, China.
  • Jie Du
    Department of Computer and Information Science, University of Macau, Macau. Electronic address: yb57415@umac.mo.
  • Jinghua Liu
    Department of Cardiology Beijing Anzhen Hospital Capital University of Medical Sciences Beijing 100029 China.

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