Artificial intelligence and machine learning in orthopedic surgery: a systematic review protocol.

Journal: Journal of orthopaedic surgery and research
Published Date: Oct 19, 2020

Abstract

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) are interwoven into our everyday lives and have grown enormously in some major fields in medicine including cardiology and radiology. While these specialties have quickly embraced AI and ML, orthopedic surgery has been slower to do so. Fortunately, there has been a recent surge in new research emphasizing the need for a systematic review. The primary objective of this systematic review will be to provide an update on the advances of AI and ML in the field of orthopedic surgery. The secondary objectives will be to evaluate the applications of AI and ML in providing a clinical diagnosis and predicting post-operative outcomes and complications in orthopedic surgery.

Authors

  • Nicola Maffulli
    Department of Musculoskeletal Disorders, School of Medicine and Surgery, University of Salerno, Fisciano, Italy.
  • Hugo C Rodriguez
    School of Osteopathic Medicine, University of the Incarnate Word, San Antonio, TX, USA.
  • Ian W Stone
    School of Osteopathic Medicine, University of the Incarnate Word, San Antonio, TX, USA.
  • Andrew Nam
  • Albert Song
    School of Osteopathic Medicine, University of the Incarnate Word, San Antonio, TX, USA.
  • Manu Gupta
    Future Biologics LLC, 1110 Ballpark Ln Apt 5109, Lawrenceville, GA, 30043, USA.
  • Rebecca Alvarado
    Texas A&M International University, Laredo, TX, USA.
  • David Ramon
    Texas A&M International University, Laredo, TX, USA.
  • Ashim Gupta
    Department of Orthopaedics, South Texas Orthopaedic Research Institute, Laredo, TX 78045, United States.

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