You are here

  • Home
  • Online First
  • Artificial intelligence in orthopaedic surgery: transforming technological innovation in patient care and surgical training

Article Text

Article menu
Download PDFPDF
Review
Artificial intelligence in orthopaedic surgery: transforming technological innovation in patient care and surgical training
  1. Jean-Pierre St Mart1,
  2. En Lin Goh2,
  3. Ignatius Liew1,
  4. Zameer Shah3,
  5. Joydeep Sinha4
  1. 1Trauma and Orthopaedics, North West Anglia NHS Foundation Trust, Peterborough, UK
  2. 2Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Oxford Trauma, Kadoorie Centre, University of Oxford, Oxford, UK
  3. 3Trauma and Orthopaedic Surgery, Guy's and St Thomas' NHS Foundation Trust, London, UK
  4. 4Trauma and Orthopaedic Surgery, King's College Hospital NHS Foundation Trust, London, UK
  1. Correspondence to Jean-Pierre St Mart, Trauma and Orthopaedics, North West Anglia NHS Foundation Trust, Peterborough, UK; jstmart{at}nhs.net

Abstract

Artificial intelligence (AI) is an exciting field combining computer science with robust data sets to facilitate problem-solving. It has the potential to transform education, practice and delivery of healthcare especially in orthopaedics. This review article outlines some of the already used AI pathways as well as recent technological advances in orthopaedics. Additionally, this article further explains how potentially these two entities could be combined in the future to improve surgical education, training and ultimately patient care and outcomes.

  • orthopaedic & trauma surgery
  • medical education & training
  • hip
  • knee

http://dx.doi.org/10.1136/postgradmedj-2022-141596

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    View Full Text

    Footnotes

    • Twitter @jpstmart

    • Contributors JS suggested, advised with the initial study, reviewed the initial drafts and helped guide the project. J-PSM is the lead principle author of the paper, wrote the questions and answers, conceived the original ideas of the paper including 'AAGs' and submitted the paper. ELG and IL helped write the paper. ZS reviewed initial draft and made suggestions.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; internally peer reviewed.