Diagnostic accuracy of deep learning in orthopaedic fractures: a systematic review and meta-analysis.

Journal: Clinical radiology
Published Date:

Abstract

AIM: To gather and compare related clinical studies, and to investigate the accuracy and reliability of deep learning in detecting orthopaedic fractures.

Authors

  • S Yang
    Neural Engineering Data Consortium, Temple University, Philadelphia, Pennsylvania, USA, {scott.yang, silvia.lopez, meysam, obeid, picone}@temple.edu.
  • B Yin
    Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China.
  • W Cao
    Shanghai Tongji Hospital, Tongji University School of Medicine, Shanghai, China.
  • C Feng
    From the Orthopedic Department, Shanghai Tenth People's Hospital (G.F., C.F., D.W., S.H.), Tongji University School of Medicine, Shanghai, China.
  • G Fan
    From the Orthopedic Department, Shanghai Tenth People's Hospital (G.F., C.F., D.W., S.H.), Tongji University School of Medicine, Shanghai, China tjhss7418@tongji.edu.cn gfan@tongji.edu.cn.
  • S He
    From the Orthopedic Department, Shanghai Tenth People's Hospital (G.F., C.F., D.W., S.H.), Tongji University School of Medicine, Shanghai, China tjhss7418@tongji.edu.cn gfan@tongji.edu.cn.