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

Authors :
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
Source :
Journal of Clinical & Translational Science; 2024 Suppl 1, Vol. 8, p98-98, 1p
Publication Year :
2024

Abstract

This document includes three abstracts from the Journal of Clinical & Translational Science. The first abstract discusses the development and validation of an artificial intelligence model to predict spinopelvic parameters in patients with adult spinal deformity. The second abstract examines the use of neuroimaging and hospitalization for transient ischemic attacks (TIAs) in the United States. The third abstract focuses on the prediction of dementia, disability, or death in elderly individuals using machine learning techniques. These abstracts provide valuable insights into the potential applications of artificial intelligence in healthcare and the management of various medical conditions. [Extracted from the article]

Details

Language :
English
ISSN :
20598661
Volume :
8
Database :
Complementary Index
Journal :
Journal of Clinical & Translational Science
Publication Type :
Academic Journal
Accession number :
176385163
Full Text :
https://doi.org/10.1017/cts.2024.289