An Introduction to Machine Learning for the Practicing Spine Surgeon.

Authors

• Ryan T Lin
• Jonathan Dalton
• Matthew H Meade
• Mark Miller
• Ruchir Nanavati
• Jarod Olson
• Joydeep Baidya
• Robert J Oris
• Barrett I Woods
• Gregory D Schroeder
• Alexander R Vaccaro

Publication/Presentation Date

8-1-2026

Abstract

The applications of new and emerging technologies in spine surgery are constantly expanding. Specifically, machine learning algorithms have seen a rise in utilization in clinical research, allowing for interpretation of large datasets that have the capability of experiential learning. The goal of this work is to present a guide for surgeons to better understand model design, key takeaways, and common pitfalls related to machine learning to ensure accurate and appropriate interpretation of analytical findings in their practice.

Volume

39

Issue

7

First Page

345

Last Page

348

ISSN

2380-0194

Published In/Presented At

Lin, R. T., Dalton, J., Meade, M. H., Miller, M., Nanavati, R., Olson, J., Baidya, J., Oris, R. J., Woods, B. I., Schroeder, G. D., & Vaccaro, A. R. (2026). An Introduction to Machine Learning for the Practicing Spine Surgeon. Clinical spine surgery, 39(7), 345–348. https://doi.org/10.1097/BSD.0000000000002026

Disciplines

Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods

PubMedID

41538248

Department(s)

Administration and Leadership

Document Type

Article