Diagnostic accuracy of machine-learning-assisted detection for anterior cruciate ligament injury based on magnetic resonance imaging: Protocol for a systematic review and meta-analysis.

Journal: Medicine
Published Date: Dec 1, 2019

Abstract

BACKGROUND: Although many machine learning algorithms have been developed to detect anterior cruciate ligament (ACL) injury based on magnetic resonance imaging (MRI), the performance of different algorithms required further investigation. The objectives of this current systematic review are to evaluate the diagnostic accuracy of machine-learning-assisted detection for ACL injury based on MRI and find the current best algorithm.

Authors

  • Yongfeng Lao
    Second Clinical Medical College of Lanzhou University.
  • Bibo Jia
    Public Health School of Lanzhou University.
  • Peilin Yan
    Jingtaixian Hospital of traditional Chinese Medicine.
  • Minghao Pan
    Second Clinical Medical College of Lanzhou University.
  • Xu Hui
    Department of Evidence-Based Medicine Centre, School of Basic Medical Science, Lanzhou University, Lanzhou, Gansu, China.
  • Jing Li
    Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
  • Wei Luo
    Centre for Pattern Recognition and Data Analytics, School of Information Technology, Deakin University, Geelong, Victoria, Australia.
  • Xingjie Li
    Second Clinical Medical College of Lanzhou University.
  • Jiani Han
    Gansu University of Chinese Medicine.
  • Peijing Yan
    Institute of Clinical Research and Evidence-Based Medicine, Gansu Provincial Hospital, Lanzhou, China.
  • Liang Yao
    Northwestern University, Chicago, IL.

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