Development of a machine learning model for identifying the optimal situation favoring double-level osteotomy over single-level high tibial osteotomy.

Journal: The Knee
PMID: 38417191

Abstract

BACKGROUND: This study aimed to develop a machine learning (ML) model to identify the optimal situation wherein double-level osteotomy (DLO) is favored for severe varus knees by analyzing unfavorable outcomes. This study hypothesized that there are the most favorable algorithms and contributing factors for identifying the optimal situation favoring DLO over opening-wedge high tibial osteotomy (OWHTO).

Authors

  • Hee Seung Nam
    Department of Orthopedic Surgery, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seoul, South Korea.
  • Jade Pei Yuik Ho
    Department of Orthopedic Surgery, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seoul, South Korea.
  • Seung Yun Park
    Department of Orthopedic Surgery, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seoul, South Korea.
  • Joon Hee Cho
    Department of Orthopedic Surgery, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seoul, South Korea.
  • Yong Seuk Lee
    Department of Orthopedic Surgery, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seoul, South Korea. Electronic address: smcos1@hanmail.net.

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