Interpretation and Reporting of Predictive or Diagnostic Machine Learning Research in Trauma & Orthopaedics

Luke Farrow* (Corresponding Author), M. Zhong, L. Anderson, G.P. Ashcroft, R. M. D. Meek

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)
3 Downloads (Pure)

Abstract

There is increasing popularity in the use of Artificial Intelligence and Machine Learning techniques to provide diagnostic and prognostic models for various aspects of Trauma and Orthopaedic surgery. Correct interpretation of these models is however difficult to those without specific knowledge of computing or health data science methodology. Lack of current reporting standards leads to potential for significant heterogeneity in the design and quality of published studies. We provide an overview of Machine Learning techniques for the “lay” individual, including key terminology and best practice reporting guidelines.
Original languageEnglish
Pages (from-to)1754-1758
Number of pages5
JournalBone and Joint Journal
Volume103B
Issue number12
DOIs
Publication statusPublished - 12 Dec 2021

Keywords

  • ARTIFICIAL-INTELLIGENCE
  • KAPPA

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