An Interpretable and Expandable Deep Learning Diagnostic System for Multiple Ocular Diseases: Qualitative Study.

Journal: Journal of medical Internet research
Published Date:

Abstract

BACKGROUND: Although artificial intelligence performs promisingly in medicine, few automatic disease diagnosis platforms can clearly explain why a specific medical decision is made.

Authors

  • Kai Zhang
    Anhui Province Key Laboratory of Respiratory Tumor and Infectious Disease, First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
  • Xiyang Liu
    School of Computer Science and Technology, Xidian University, No. 2 South Taibai Rd, Xi'an, 710071, China. xyliu@xidian.edu.cn.
  • Fan Liu
    Hunan Provincial Key Laboratory of Dong Medicine, Hunan University of Medicine, Huaihua, China.
  • Lin He
    College of Plant Protection, Southwest University, Chongqing, China.
  • Lei Zhang
    Division of Gastroenterology, Union Hospital, Tongji Medical College Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Yahan Yang
    University of Pennsylvania, Philadelphia, PA.
  • Wangting Li
    State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Xian Lie South Road 54#, Guangzhou, 510060, China.
  • Shuai Wang
    Department of Intensive Care Unit, China-Japan Union Hospital of Jilin University, Changchun, China.
  • Lin Liu
    Institute of Natural Sciences, MOE-LSC, School of Mathematical Sciences, CMA-Shanghai, SJTU-Yale Joint Center for Biostatistics and Data Science, Shanghai Jiao Tong University; Shanghai Artificial Intelligence Laboratory.
  • Zhenzhen Liu
    Department of Functional Science, School of Medicine, Yangtze University, No.1 Nanhuan Road, Jingzhou City 434100, China.
  • Xiaohang Wu
    State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Xian Lie South Road 54#, Guangzhou, 510060, China.
  • Haotian Lin
    State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou.