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This review aims to evaluate the effectiveness of AI in diagnosing traumatic femur fractures compared to human assessment.

February 28, 2026Open Access

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

Key Points

This review aims to evaluate the effectiveness of AI in diagnosing traumatic femur fractures compared to human assessment.
Conducted a systematic review and meta-analysis of existing studies
Compared diagnostic accuracy of AI algorithms with that of human radiologists
Evaluated various AI algorithms used in trauma settings
AI demonstrated comparable or superior performance to human experts in identifying femur fractures
Identified specific strengths of AI in accuracy and speed
Pointed out areas where AI performance is weaker, highlighting potential improvement needs

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.

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Audrey Banks

A E Gharavi

Matthew Gish

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

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Abstract

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