Clinical application of an automatic facial recognition system based on deep learning for diagnosis of Turner syndrome.

Journal: Endocrine
PMID: 33170449

Abstract

PURPOSE: Automated facial recognition technology based on deep learning has achieved high accuracy in diagnosing various endocrine diseases and genetic syndromes. This study attempts to establish a facial diagnostic system for Turner syndrome (TS) based on deep convolutional neural networks.

Authors

  • Zhouxian Pan
    Department of Allergy, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences & Peking Union Medical College (CAMS & PUMC), 100730, Beijing, China.
  • Zhen Shen
    Institute of Machine Learning and Systems Biology, School of Electronics and Information Engineering, Tongji University, Shanghai, 201804, P. R. China.
  • Huijuan Zhu
    Department of Endocrinology, Chinese Academy of Medical Sciences and Peking Union Medical College, Peking Union Medical College Hospital, Beijing, China.
  • Yin Bao
    State Key Laboratory for Management and Control of Complex Systems, Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China.
  • Siyu Liang
    Department of Endocrinology, Endocrine Key Laboratory of Ministry of Health, PUMCH, CAMS & PUMC, 100730, Beijing, China.
  • Shirui Wang
    Eight-year Program of Clinical Medicine, Peking Union Medical College Hospital (PUMCH), Chinese Academe of Medical Sciences & Peking Union Medical College (CAMS & PUMC), Beijing, China.
  • Xiangying Li
    Department of Endocrinology, Endocrine Key Laboratory of Ministry of Health, PUMCH, CAMS & PUMC, 100730, Beijing, China.
  • Lulu Niu
    State Key Laboratory for Management and Control of Complex Systems, Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China.
  • Xisong Dong
    State Key Laboratory for Management and Control of Complex Systems, Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China.
  • Xiuqin Shang
    State Key Laboratory for Management and Control of Complex Systems, Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China.
  • Shi Chen
    Department of Endocrinology, Key Laboratory of Endocrinology of National Health Commission, PUMCH, CAMS & PUMC, Beijing, China.
  • Hui Pan
    Department of Endocrinology, Key Laboratory of Endocrinology of National Health Commission, PUMCH, CAMS & PUMC, Beijing, China.
  • Gang Xiong
    Department of Information, The Second Affiliated Hospital of Nanchang University, Nanchang, China.

Keywords

External Resources

Popular Topics
Recent Journals