RT Journal Article
SR Electronic
T1 Artificial Intelligence and Machine Learning Applications in Spine Surgery
JF International Journal of Spine Surgery
JO Int J Spine Surg
FD International Society for the Advancement of Spine Surgery
SP 8503
DO 10.14444/8503
A1 Nathan J. Lee
A1 Joseph M. Lombardi
A1 Ronald A. Lehman
YR 2023
UL http://ijssurgery.com//content/early/2023/05/11/8503.abstract
AB The complexity of patients with spine pathology and high rates of complications has driven extensive research directed toward optimizing outcomes and reducing complications. Traditional statistical analysis has been limited both in validity and in the number of predictor variables considered. Over the past decade, artificial intelligence and machine learning have taken center stage as the possible solution to creating more accurate and applicable patient-centered predictive models in spine surgery. This review discusses the current published machine learning applications on preoperative optimization, risk stratification, and predictive modeling for the cervical, lumbar, and adult spinal deformity populations.