Smart identification of psoriasis by images using convolutional neural networks: a case study in China.

Journal: Journal of the European Academy of Dermatology and Venereology : JEADV
Published Date: Oct 17, 2019

Abstract

BACKGROUND: Psoriasis is a chronic inflammatory skin disease, which holds a high incidence in China. However, professional dermatologists who can diagnose psoriasis early and correctly are insufficient in China, especially in the rural areas. A smart approach to identify psoriasis by pictures would be highly adaptable countrywide and could play a useful role in early diagnosis and regular treatment of psoriasis.

Authors

  • S Zhao
    Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.
  • B Xie
    School of Information Science and Engineering, Central South University, Changsha, China.
  • Y Li
  • X Zhao
    Department of Animal Science, McGill University, Sainte-Anne-de-Bellevue, Quebec, Canada H9X 3V9.
  • Y Kuang
    Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.
  • J Su
    Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.
  • X He
  • X Wu
    Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark.
  • W Fan
    Tencent Medical AI Lab, Beijing, China.
  • K Huang
    Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.
  • Y Peng
    Department of Epidemiology and Health Statistics,Guangdong Pharmaceutical University,Guangzhou,China.
  • A A Navarini
    Department of Dermatology, University Hospital of Basel, Basel, Switzerland.
  • W Huang
    Mobile Health Ministry of Education - China Mobile Joint Laboratory, Xiangya Hospital, Central South University, Changsha, China.
  • X Chen
    Division of Infectious Diseases,The People's Hospital of Meizhou,Meizhou,China.

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