Research Progress of Machine Learning and Deep Learning in Intelligent Diagnosis of the Coronary Atherosclerotic Heart Disease.

Journal: Computational and mathematical methods in medicine
Published Date:

Abstract

The coronary atherosclerotic heart disease is a common cardiovascular disease with high morbidity, disability, and societal burden. Early, precise, and comprehensive diagnosis of the coronary atherosclerotic heart disease is of great significance. The rise of artificial intelligence technologies, represented by machine learning and deep learning, provides new methods to address the above issues. In recent years, artificial intelligence has achieved an extraordinary progress in multiple aspects of coronary atherosclerotic heart disease diagnosis, including the construction of intelligent diagnostic models based on artificial intelligence algorithms, applications of artificial intelligence algorithms in coronary angiography, coronary CT angiography, intravascular imaging, cardiac magnetic resonance, and functional parameters. This paper presents a comprehensive review of the technical background and current state of research on the application of artificial intelligence in the diagnosis of the coronary atherosclerotic heart disease and analyzes recent challenges and perspectives in this field.

Authors

  • Haoxuan Lu
    The Affiliated Hospital of Medical School, Ningbo University, Ningbo 315020, China.
  • Yudong Yao
    Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, China.
  • Li Wang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Jianing Yan
    The Affiliated Hospital of Medical School, Ningbo University, Ningbo 315020, China.
  • Shuangshuang Tu
    The Affiliated Hospital of Medical School, Ningbo University, Ningbo 315020, China.
  • Yanqing Xie
    The Affiliated Hospital of Medical School, Ningbo University, Ningbo 315020, China.
  • Wenming He
    The Affiliated Hospital of Medical School, Ningbo University, Ningbo 315020, China.