Revolutionizing Spine Surgery: The Potential Role of AI in Enhancing Surgical Workflow and Patient Outcomes

Authors

Samuel Ezeonu, Thomas Jefferson UniversityFollow

Abstract

Introduction

With the growing incidence of degenerative spine pathology¹, surgeons have been tasked to treat more patients than ever. According to Mani et al., the number of single and multilevel fusion procedures are both projected to double over the next 25 years.² In light of this trend, several strategies have been proposed to reduce the resultant burden placed on hospitals and surgeons, while maintaining optimal standards of care. Namely, the use of artificial intelligence (AI) is a growing field that has greatly increased in the last decade. AI has the potential to relieve the cognitive workload placed on health providers in daily practice to make patient care more efficient and improve outcomes.

In simple terms, AI refers to the reproduction of human intelligence and cognitive function through the use of computerized systems and programs via inputted data and algorithms.³ Specifically, machine learning (ML) is a subset of AI in which systems can learn through analyses of large datasets and develop complex analytic and prognostic models. The most common type of learning used in medicine is classified as a supervised machine learning strategy⁴, where the model is trained on “labeled data.” Each input has a corresponding correct output, and the ML system is “taught” to understand the features of the inputted data. The most common supervised ML models include deep learning (DL), artificial neural networks (ANNs), convolutional neural networks (CNNs), decision trees/random forests, support vector machines (SVM), and image recognition applications.^4-6

Given the universal adoption of electronic health records, AI can be enabled as a capable tool to improve the effectiveness of health operations and make the interpretation of previous indeterminable clinical patterns a much more feasible task.⁷ Particularly in the context of spine surgery, AI can aid in preoperative workup and surgical planning, intraoperative execution and efficiency, and predictive modeling of prognostic outcomes.

Recommended Citation

Ezeonu, Samuel (2025) "Revolutionizing Spine Surgery: The Potential Role of AI in Enhancing Surgical Workflow and Patient Outcomes," Bone Bulletin: Vol. 3: Iss. 1, Article 6.
Available at: https://jdc.jefferson.edu/bone_bulletin/vol3/iss1/6