Artificial Intelligence Performance in Image-Based Cancer Identification: Umbrella Review of Systematic Reviews.

Journal: Journal of medical Internet research
PMID:

Abstract

BACKGROUND: Artificial intelligence (AI) has the potential to transform cancer diagnosis, ultimately leading to better patient outcomes.

Authors

  • He-Li Xu
    Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China.
  • Ting-Ting Gong
    Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China. Electronic address: gongtt@sj-hospital.org.
  • Xin-Jian Song
    Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China.
  • Qian Chen
    Department of Pain Medicine Guizhou Provincial Orthopedics Hospital Guiyang Guizhou China.
  • Qi Bao
    The First Affiliated Hospital of Naval Military Medical University, Shanghai, 200433.
  • Wei Yao
    Department of Respiratory Medicine, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Meng-Meng Xie
    Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
  • Chen Li
    School of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
  • Marcin Grzegorzek
    Institute for Vision and Graphics, University of Siegen, Hoerlindstr. 3, 57076 Siegen, Germany.
  • Yu Shi
    NIH BD2K Program Centers of Excellence for Big Data Computing-KnowEng Center, Department of Computer Science, University of Illinois at Urbana-Champaign , Champaign, Illinois.
  • Hong-Zan Sun
    Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China. sunhongzan@126.com.
  • Xiao-Han Li
    MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK.
  • Yu-Hong Zhao
    Department of Clinical Epidemiology, Clinical Research Center, Shengjing Hospital, China Medical University, Shenyang, 110004, China. zhaoyuhong@sj-hospital.org.
  • Song Gao
    Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Qi-Jun Wu
    Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China; Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Reproductive and Genetic Medicine (China Medical University), National Health Commission, Shenyang, China. Electronic address: wuqj@sj-hospital.org.