OBJECTIVE In recent years, machine learning models for clinical prediction have become
increasingly prevalent in the neurosurgical literature. However, little is known about the …

Clinical prediction models for spine surgery applications are on the rise, with an increasing
reliance on machine learning (ML) and deep learning (DL). Many of the predicted outcomes …

Study Design: A retrospective cohort study from a multisite academic medical center.
Objective: To construct, evaluate, and interpret a series of machine learning models to …

Artificial intelligence (AI) is transforming spinal imaging and patient care through automated
analysis and enhanced decision-making. This review presents a clinical task-based …

Background Risk assessment is critically important in elective and high-risk interventions,
particularly spine surgery. This narrative review describes the evolution of risk assessment …

While spine surgery has historically been performed in the inpatient setting, in recent years
there has been growing interest in performing certain cervical and lumbar spine procedures …

Artificial intelligence and machine learning (ML) can offer revolutionary advances in their
application to the field of spine surgery. Within the past 5 years, novel applications of ML …

Decision-making in spine surgery is complex due to patients' heterogeneity and complexity
of spinal pathologies and the various surgical options applied to a given pathology. Artificial …

As hospital costs associated with spine surgeries continue to climb, length of stay (LOS) and
discharge disposition have been utilized as proxies through which these increasing costs …

INTRODUCTION: Artificial intelligence (AI) and machine learning (ML) techniques have
become highly visible in society and medicine, with some AI/ML-enabled devices receiving …