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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Veröffentlicht in:	Journal of clinical and translational science Jg. 8; H. s1; S. 98
Hauptverfasser:	Harake, Edward S, Linzey, Joseph R., Jiang, Cheng, Jones, Jaes C., Joshi, Rushikesh, Zaki, Mark, Wilseck, Zachary, Joseph, Jacob, Hollon, Todd, Khalsa, Siri Sahib S., Park, Paul
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cambridge Cambridge University Press 01.04.2024
Schlagworte:	Artificial intelligence Informatics and Data Science Population studies Scholarships & fellowships Spine (lumbar) Surgeons X-rays
ISSN:	2059-8661, 2059-8661
Online-Zugang:	Volltext
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