Artificial intelligence facial recognition system for diagnosis of endocrine and metabolic syndromes based on a facial image database.

Journal: Diabetes & metabolic syndrome
Published Date:

Abstract

AIM: To build a facial image database and to explore the diagnostic efficacy and influencing factors of the artificial intelligence-based facial recognition (AI-FR) system for multiple endocrine and metabolic syndromes.

Authors

  • Danning Wu
    Key Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, 100142, China.
  • Jiaqi Qiang
    Key Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
  • Weixin Hong
    State Key Laboratory of Multimodal Artificial Intelligence Systems, Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China.
  • Hanze Du
    Key Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
  • Hongbo Yang
    Fuwai Yunnan Hospital, Chinese Academy of Medical Sciences, Affiliated Cardiovascular Hospital of Kunming Medical University, Kunming, China.
  • Huijuan Zhu
    Department of Endocrinology, Chinese Academy of Medical Sciences and Peking Union Medical College, Peking Union Medical College Hospital, Beijing, China.
  • Hui Pan
    Department of Endocrinology, Key Laboratory of Endocrinology of National Health Commission, PUMCH, CAMS & PUMC, Beijing, China.
  • Zhen Shen
    Institute of Machine Learning and Systems Biology, School of Electronics and Information Engineering, Tongji University, Shanghai, 201804, P. R. China.
  • Shi Chen
    Department of Endocrinology, Key Laboratory of Endocrinology of National Health Commission, PUMCH, CAMS & PUMC, Beijing, China.