The development and deployment of machine learning models.

Journal: Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Published Date: Sep 9, 2022

Abstract

Applications of artificial intelligence, specifically machine learning, are becoming increasingly popular in Orthopaedic Surgery, and medicine as a whole. This growing interest is shared by data scientists and physicians alike. However, there is an asymmetry of understanding of the developmental process and potential applications of machine learning. As new technology will undoubtedly affect clinical practice in the coming years, it is important for physicians to understand how these processes work. The purpose of this paper is to provide clarity and a general framework for building and assessing machine learning models.

Authors

  • James A Pruneski
    Department of Orthopedic Surgery, Boston Children's Hospital, Boston, MA, USA.
  • Riley J Williams
    Department of Orthopaedic Surgery, Hospital for Special Surgery, New York, New York, U.S.A.
  • Benedict U Nwachukwu
    Department of Orthopaedic Surgery, Hospital for Special Surgery, New York, New York, U.S.A.
  • Prem N Ramkumar
    Department of Orthopedic Surgery, Cleveland Clinic, Cleveland, OH.
  • Ata M Kiapour
    Department of Orthopaedic Surgery and Sports Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
  • R Kyle Martin
    Department of Orthopaedic Surgery, University of Minnesota, Minneapolis, Minnesota, USA rkylemmartin@gmail.com.
  • Jón Karlsson
    Orthopaedic Research Department, Göteborg University, Göteborg, SE, Sweden.
  • Ayoosh Pareek
    Department of Orthopaedic Surgery and Sports Medicine, Mayo Clinic, Rochester, Minnesota, USA.

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