Publikation

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

Wissenschaftlicher Artikel/Review - 24.02.2024

Bereiche
PubMed
DOI
Kontakt

Zitation
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
Art
Wissenschaftlicher Artikel/Review (Englisch)
Zeitschrift
World Neurosurg 2024
Veröffentlichungsdatum
24.02.2024
eISSN (Online)
1878-8769
Kurzbeschreibung/Zielsetzung

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.