Managing class imbalance in the training of a large language model to predict patient selection for total knee arthroplasty: Results from the Artificial intelligence to Revolutionise the patient Care pathway in Hip and knEe aRthroplastY (ARCHERY) project.

Journal: The Knee
Published Date:

Abstract

INTRODUCTION: This study set out to test the efficacy of different techniques used to manage to class imbalance, a type of data bias, in application of a large language model (LLM) to predict patient selection for total knee arthroplasty (TKA).

Authors

  • Luke Farrow
    University of Aberdeen, Aberdeen, UK.
  • Lesley Anderson
    University of Aberdeen, Aberdeen, UK.
  • Mingjun Zhong
    University of Aberdeen, Aberdeen, UK.