Comprehensive AI-assisted tool for ankylosing spondylitis based on multicenter research outperforms human experts.

Journal: Frontiers in public health
PMID:

Abstract

INTRODUCTION: The diagnosis and treatment of ankylosing spondylitis (AS) is a difficult task, especially in less developed countries without access to experts. To address this issue, a comprehensive artificial intelligence (AI) tool was created to help diagnose and predict the course of AS.

Authors

  • Hao Li
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Xiang Tao
    Department of Pathology, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, China.
  • Tuo Liang
    The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Jie Jiang
    Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, P. R. China.
  • Jichong Zhu
    Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, P.R. China.
  • Shaofeng Wu
    Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, P.R. China.
  • Liyi Chen
    The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Zide Zhang
    The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Chenxing Zhou
    Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, P.R. China.
  • Xuhua Sun
    The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Shengsheng Huang
    The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Jiarui Chen
    Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macau, China.
  • Tianyou Chen
    Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, P.R. China.
  • Zhen Ye
    School of Medicine, Collaborative Innovation Center for Biotherapy, Nankai University, 94 Weijin Road, Tianjin, 300071, China.
  • Wuhua Chen
    The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Hao Guo
    College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China.
  • Yuanlin Yao
    Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, P.R. China.
  • Shian Liao
    The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Chaojie Yu
    The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Binguang Fan
    The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Yihong Liu
    School of Computer Science, Huainan Normal University, Huainan, China.
  • Chunai Lu
    Guangxi Medical University, Nanning, Guangxi, China.
  • Junnan Hu
    Department of Computer, School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB), Beijing 100083, China.
  • Qinghong Xie
    Guangxi Medical University, Nanning, Guangxi, China.
  • Xiao Wei
    Guangxi Medical University, Nanning, Guangxi, China.
  • Cairen Fang
    Guangxi Medical University, Nanning, Guangxi, China.
  • Huijiang Liu
    Orthopaedics of The First People's Hospital of Nanning, Nanning, Guangxi, China.
  • Chengqian Huang
    Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, P.R. China.
  • Shixin Pan
    Orthopaedics of Wuzhou Red Cross Hospital, Wuzhou, Guangxi, China.
  • Xinli Zhan
    Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, P.R. China.
  • Chong Liu
    * Department of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, P. R. China.