Predictive modeling of complications.
Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions.
Department of Neurological Surgery, University of California, 505 Parnassus Ave. Rm. M779, San Francisco, CA, 94143-0112, USA. osorioj@neurosurg.ucsf.edu.
Joseph A
JA
Osorio
School of Medicine, University of California, La Jolla, San Diego, CA, USA.
Justin K
JK
Scheer
Department of Neurological Surgery, University of California, 505 Parnassus Ave. Rm. M779, San Francisco, CA, 94143-0112, USA.
Christopher P
CP
Ames
Adult spinal deformity; Logistic regression; Predictive analytics; Predictive modeling; Surgical complications