PT  - JOURNAL ARTICLE
AU  - Lee, Nathan J.
AU  - Lombardi, Joseph M.
AU  - Lehman, Ronald A.
TI  - Artificial Intelligence and Machine Learning Applications in Spine Surgery
AID  - 10.14444/8503
DP  - 2023 May 12
TA  - International Journal of Spine Surgery
PG  - 8503
4099  - https://www.ijssurgery.com/content/early/2023/05/11/8503.short
4100  - https://www.ijssurgery.com/content/early/2023/05/11/8503.full
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.