Assessment of Automated Identification of Phases in Videos of Total Hip Arthroplasty Using Deep Learning Techniques.

Journal: Clinics in orthopedic surgery
PMID: 38562629

Abstract

BACKGROUND: As the population ages, the rates of hip diseases and fragility fractures are increasing, making total hip arthroplasty (THA) one of the best methods for treating elderly patients. With the increasing number of THA surgeries and diverse surgical methods, there is a need for standard evaluation protocols. This study aimed to use deep learning algorithms to classify THA videos and evaluate the accuracy of the labelling of these videos.

Authors

  • Yang Jae Kang
    Division of Bio and Medical Big Data Department (BK4 Program) and Life Science Department, Gyeongsang National University, Jinju, Korea.
  • Shin June Kim
    Biomedical Research Institute, Inha University Hospital, Incheon, Korea.
  • Sung Hyo Seo
    Biomedical Research Institute, Gyeongsang National University Hospital, Jinju, Korea.
  • Sangyeob Lee
    Biomedical Research Institute, Gyeongsang National University Hospital, Jinju, Korea.
  • Hyeon Su Kim
    Department of Orthopedic Surgery, Inha University Hospital, Inha University College of Medicine, Incheon, South Korea.
  • Jun-Il Yoo
    Department of Orthopedic Surgery, Inha University Hospital, Inha University College of Medicine, Incheon, South Korea.

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