Feasibility of using deep learning to detect coronary artery disease based on facial photo.

Journal: European heart journal
Published Date:

Abstract

AIMS: Facial features were associated with increased risk of coronary artery disease (CAD). We developed and validated a deep learning algorithm for detecting CAD based on facial photos.

Authors

  • Shen Lin
    Department of Neurobiology, Key Laboratory of Medical Neurobiology of Ministry of Health, Zhejiang Province Key Laboratory of Neurobiology, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China.
  • Zhigang Li
    Hefei Institute of Physical Science, Chinese Academy of Sciences Hefei 230036 PR China liuyong@aiofm.ac.cn zhanglong@aiofm.ac.cn wangchongwen1987@126.com.
  • Bowen Fu
    Department of Automation, Tsinghua University, Main building, Haidian District, Beijing 100084, People's Republic of China.
  • Sipeng Chen
    School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069.
  • Xi Li
  • Yang Wang
    Department of General Surgery The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology Kunming China.
  • Xiaoyi Wang
    Department of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
  • Bin Lv
    Ping An Healthcare Technology, Shang Hai, PR China.
  • Bo Xu
    State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China.
  • Xiantao Song
    Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, No. 2 Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China.
  • Yao-Jun Zhang
    Department of Cardiology, Xuzhou Third People's Hospital, Xuzhou Medical University, No. 131 Huancheng Road, Huaihai Economy District, Xuzhou 221000, People's Republic of China.
  • Xiang Cheng
    Computer Department, Jingdezhen Ceramic Institute, Jingdezhen, China.
  • Weijian Huang
    Department of Cardiology, The First Affiliated Hospital of Wenzhou Medical University, Nanbaixiang Road, Ouhai District, Wenzhou 325000, People's Republic of China.
  • Jun Pu
    Center for the Science of Therapeutics, Broad Institute of Harvard and MIT , 7 Cambridge Center, Cambridge, Massachusetts 02142, United States.
  • Qi Zhang
    Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Yunlong Xia
    Department of Cardiology, First Affiliated Hospital of Dalian Medical University, 116011 Dalian, Liaoning, China.
  • Bai Du
    Department of Cardiology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No.5 Beixiange Road, Xicheng District, Beijing 100053, People's Republic of China.
  • Xiangyang Ji
    Department of Automation, Tsinghua University, Main building, Haidian District, Beijing 100084, People's Republic of China.
  • Zhe Zheng
    National Clinical Research Center of Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 167 Beilishi Road, Xicheng District, Beijing 100037, People's Republic of China.