319 Development and Validation of an Artificial Intelligence Model to Accurately Predict Spinopelvic Parameters

319 Development and Validation of an Artificial Intelligence Model to Accurately Predict Spinopelvic Parameters

OBJECTIVES/GOALS: The correction of spinopelvic parameters is associated with better outcomes in patients with adult spinal deformity (ASD). This study presents a novel artificial intelligence (AI) tool that automatically predicts spinopelvic parameters from spine x-rays with high accuracy and witho...

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Bibliographic Details
Main Authors: Edward S Harake, Joseph R. Linzey, Cheng Jiang, Jaes C. Jones, Rushikesh Joshi, Mark Zaki, Zachary Wilseck, Jacob Joseph, Todd Hollon, Siri Sahib S. Khalsa, Paul Park
Format: Article
Language:English
Published: Cambridge University Press 2024-04-01
Series:Journal of Clinical and Translational Science
Online Access:https://www.cambridge.org/core/product/identifier/S2059866124002899/type/journal_article

Internet

https://www.cambridge.org/core/product/identifier/S2059866124002899/type/journal_article

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