TKA-AID: An Uncertainty-Aware Deep Learning Classifier to Identify Total Knee Arthroplasty Implants.

Journal: The Journal of arthroplasty
Published Date: Jan 19, 2025

Abstract

BACKGROUND: A drastic increase in the volume of primary total knee arthroplasties (TKAs) performed nationwide will inevitably lead to higher volumes of revision TKAs in which the primary knee implant must be removed. An important step in preoperative planning for revision TKA is implant identification, which is time-consuming and difficult even for experienced surgeons. We sought to develop a deep learning algorithm to automatically identify the most common models of primary TKA implants.

Authors

  • Kellen L Mulford
    Department of Orthopedic Surgery, Orthopedic Surgery Artificial Intelligence Laboratory, Mayo Clinic, Rochester, Minnesota.
  • Sami Saniei
    Mayo Clinic, Rochester, MN, USA.
  • Elizabeth S Kaji
    Orthopedic Surgery Artificial Intelligence Laboratory (OSAIL), Department of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota.
  • Austin F Grove
    Mayo Clinic, Rochester, Minnesota.
  • Miguel Girod-Hoffman
    Mayo Clinic, Rochester, MN, USA.
  • Pouria Rouzrokh
    Department of Radiology, Mayo Clinic, Radiology Informatics Laboratory, Rochester, MN.
  • Matthew P Abdel
    Mayo Clinic Department of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota.
  • Michael J Taunton
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN; Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN.
  • Cody C Wyles
    Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN.

Keywords

External Resources

Popular Topics
Recent Journals