Machine Learning for the Prediction of Cervical Spondylotic Myelopathy: A Post Hoc Pilot Study of 28 Participants.

Journal: World neurosurgery
PMID: 30922901

Abstract

BACKGROUND: Cervical spondylotic myelopathy (CSM) severity and presence of symptoms are often difficult to predict based simply on clinical imaging alone. Similarly, improved machine learning techniques provide new tools with immense clinical potential.

Authors

  • Benjamin S Hopkins
    Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
  • Kenneth A Weber
    Department of Radiology, Stanford University School of Medicine, Stanford, California, USA.
  • Kartik Kesavabhotla
    Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
  • Monica Paliwal
    Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
  • Donald R Cantrell
    Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
  • Zachary A Smith
    Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA. Electronic address: zsmith1@nm.org.

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