Predictive Model for Selection of Upper Treated Vertebra Using a Machine Learning Approach.

Journal: World neurosurgery
Published Date: Oct 19, 2020

Abstract

OBJECTIVE: To train and validate an algorithm mimicking decision making of experienced surgeons regarding upper instrumented vertebra (UIV) selection in surgical correction of thoracolumbar adult spinal deformity.

Authors

  • Renaud Lafage
    Spine Research Laboratory, Hospital for Special Surgery, 535 E 71st Street, New York, NY, 10021, USA.
  • Bryan Ang
    Department of Spine Surgery, Hospital for Special Surgery, Department of Spine Surgery, New York, New York, USA. Electronic address: Bka2001@med.cornell.edu.
  • Basel Sheikh Alshabab
    Department of Spine Surgery, Hospital for Special Surgery, Department of Spine Surgery, New York, New York, USA.
  • Jonathan Elysee
    Department of Spine Surgery, Hospital for Special Surgery, Department of Spine Surgery, New York, New York, USA.
  • Francis Lovecchio
    Hospital for Special Surgery, New York, NY.
  • Karen Weissman
    Department of Spine Surgery, Hospital for Special Surgery, Department of Spine Surgery, New York, New York, USA.
  • Han Jo Kim
    Department of Orthopaedic Surgery, Hospital for Special Surgery, New York, New York, USA.
  • Frank Schwab
    Department of Orthopaedic Surgery, NYU Hospital for Joint Diseases, 306 E 15th Street, Suite 1F, New York, NY 10003, USA.
  • Virginie Lafage
    Department of Orthopaedic Surgery, NYU Hospital for Joint Diseases, 306 E 15th Street, Suite 1F, New York, NY 10003, USA.

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