Publication

Deep Learning Prediction of Cervical Spine Surgery Revision Outcomes Using Standard Laboratory and Operative Variables.

Journal Paper/Review - Feb 24, 2024

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Citation
Schonfeld E, Shah A, Johnstone T, Rodrigues A, Morris G, Stienen M, Veeravagu A. Deep Learning Prediction of Cervical Spine Surgery Revision Outcomes Using Standard Laboratory and Operative Variables. World Neurosurg 2024
Type
Journal Paper/Review (English)
Journal
World Neurosurg 2024
Publication Date
Feb 24, 2024
Issn Electronic
1878-8769
Brief description/objective

Cervical spine procedures represent a major proportion of all spine surgery. Mitigating the revision rate following cervical procedures requires careful patient selection. While complication risk has successfully been predicted, revision risk has proven more challenging. This is likely due to the absence of granular variables in claims databases. The objective of this study was to develop a state-of-the-art of revision prediction of cervical spine surgery using laboratory and operative variables.