Deep learning in spine surgery

Hamid Ghaednia, Amanda Lans, Nicholas Sauder, David Shin, William G. Grant, Rohan R. Chopra, Jacobien H.F. Oosterhoff, Mitchell S. Fourman, Joseph H. Schwab, Daniel G. Tobert

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Deep learning is increasingly impactful for healthcare research and delivery. In orthopaedics, there has been a significant increase in the number of publications using deep learning for interpreting radiographs; however, there are only a few applications of deep learning specific to spine surgery. In this review, we discuss the potential of deep learning within spine surgery in four contexts: diagnosis (1), prognosis (2), patient management (3) and integration with virtual/augmented reality, robotic surgery and biomedical wearables (4). Additionally, we discuss current literature, future potentials and provide takeaways for clinicians who wish to apply deep learning in their research and practice.

Original languageEnglish (US)
Article number100876
JournalSeminars in Spine Surgery
Volume33
Issue number2
DOIs
StatePublished - Jun 2021
Externally publishedYes

ASJC Scopus subject areas

  • Surgery
  • Orthopedics and Sports Medicine

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