Artificial intelligence-based assessment of leg axis parameters shows excellent agreement with human raters: A systematic review and meta-analysis.

Journal: Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PMID: 39033340

Abstract

PURPOSE: The aim of this study was to conduct a systematic review and meta-analysis on the reliability and applicability of artificial intelligence (AI)-based analysis of leg axis parameters. We hypothesized that AI-based leg axis measurements would be less time-consuming and as accurate as those performed by human raters.

Authors

  • Mikhail Salzmann
    Center of Orthopaedics and Traumatology, Brandenburg Medical School, University Hospital Brandenburg an der Havel, Brandenburg an der Havel, Germany.
  • Hakam Hassan Tarek
    Center of Orthopaedics and Traumatology, Brandenburg Medical School, University Hospital Brandenburg an der Havel, Brandenburg an der Havel, Germany.
  • Robert Prill
    Center of Orthopaedics and Traumatology, Brandenburg Medical School, University Hospital Brandenburg an der Havel, Brandenburg an der Havel, Germany.
  • Roland Becker
    Center of Orthopaedics and Traumatology, Brandenburg Medical School, University Hospital Brandenburg an der Havel, Brandenburg an der Havel, Germany.
  • Andreas G Schreyer
    Institute for Diagnostic and Interventional Radiology, Brandenburg Medical School Theodor Fontane, Brandenburg an der Havel, Germany.
  • Robert Hable
    Faculty of Applied Computer Science, Deggendorf Institute of Technology, Deggendorf, Germany.
  • Marko Ostojic
    Department of Orthopedics, University Hospital Mostar, Mostar, Bosnia and Herzegovina.
  • Nikolai Ramadanov
    Center of Orthopaedics and Traumatology, Brandenburg Medical School, University Hospital Brandenburg an der Havel, Brandenburg an der Havel, Germany.

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