Machine Learning Algorithms Predict Functional Improvement After Hip Arthroscopy for Femoroacetabular Impingement Syndrome in Athletes.

Journal: The Journal of bone and joint surgery. American volume
PMID: 33877058

Abstract

BACKGROUND: Despite previous reports of improvements for athletes following hip arthroscopy for femoroacetabular impingement syndrome (FAIS), many do not achieve clinically relevant outcomes. The purpose of this study was to develop machine learning algorithms capable of providing patient-specific predictions of which athletes will derive clinically relevant improvement in sports-specific function after undergoing hip arthroscopy for FAIS.

Authors

  • Kyle N Kunze
    Department of Orthopedic Surgery, Hospital for Special Surgery, New York, NY, USA.
  • Evan M Polce
    Department of Orthopaedic Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
  • Ian Clapp
    Division of Sports Medicine, Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, Illinois.
  • Benedict U Nwachukwu
    Department of Orthopaedic Surgery, Hospital for Special Surgery, New York, New York, U.S.A.
  • Jorge Chahla
    Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, Illinois, U.S.A.. Electronic address: jachahla@msn.com.
  • Shane J Nho
    Departments of Sports Medicine and Orthopedic Surgery, Rush University Medical Center, Chicago, IL, USA.

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