An artificial intelligence-based risk prediction model of myocardial infarction.

Journal: BMC bioinformatics
Published Date: Jun 7, 2022

Abstract

BACKGROUND: Myocardial infarction can lead to malignant arrhythmia, heart failure, and sudden death. Clinical studies have shown that early identification of and timely intervention for acute MI can significantly reduce mortality. The traditional MI risk assessment models are subjective, and the data that go into them are difficult to obtain. Generally, the assessment is only conducted among high-risk patient groups.

Authors

  • Ran Liu
    Department of Neurology, Xiangya Hospital, Central South University, Jiangxi, Nanchang, 330006, Jiangxi, China.
  • Miye Wang
  • Tao Zheng
    Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, People's Republic of China; Key Laboratory of Renewable Energy, Chinese Academy of Sciences, Guangzhou 510640, People's Republic of China. Electronic address: zhengtao@ms.giec.ac.cn.
  • Rui Zhang
    Department of Cardiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
  • Nan Li
    School of Basic Medical Sciences, Jiamusi University No. 258, Xuefu Street, Xiangyang District, Jiamusi 154007, Heilongjiang, China.
  • Zhongxiu Chen
    Department of Cardiology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China.
  • Hongmei Yan
    Ministry of Education Key Laboratory of Metabolism and Molecular Medicine, Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China.
  • Qingke Shi
    Engineering Research Center of Medical Information Technology, Ministry of Education, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China. shiqingke@wchscu.cn.

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