Diagnostic Performance of AI in Traumatic Femur Fracture: A Systematic Review and Meta-Analysis

2026 Preprint Open access

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Authors: Audrey Bankes, A E Gharavi, Matthew Gish, Andrew Tom, Michele T. McGinnis, Mohanad K Abou Chaar, Daniel Stephens, Ashish Khandelwal, Cody C. Wyles, George Thomas, Anna L. Lundeen, Sergio Michael Navarro
+1 more Krystin A. Hidden
DOI: 10.17605/osf.io/uv4kt
Cited by: 0

Abstract

This systematic review and meta analysis compares AI capabilities to human abilities at identifying femur fractures in a trauma setting. This information closes a knowledge gap in current AI applications in trauma imaging and may reveal potential areas of application for AI in clinical settings. Overall, this project will provide clinicians with information on the utility of AI in traumatic femur fracture identification and will identify areas of strength and weakness of AI systems.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Bone fractures and treatments Medical Imaging and Analysis

Publication details

Publication date
1 January 2026
Language
EN
Document type
Preprint