Effectiveness of an Artificial Intelligence Software for Limb Radiographic Fracture Recognition in an Emergency Department

BoneView

Published in Journal of Clinical Medicine September 2024

Authors Herpe G, Nelken H, Vendeuvre T, Guenezan J, Giraud C, Mimoz O, Feydy A, Tasu J-P, Guillevin R

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Objective:

Assessment of the impact of an Artificial Intelligence (AI) limb bone fracture diag-4 nosis software (AIS) on emergency department (ED) workflow and diagnostic accuracy.

Methods:

A retrospective study was conducted in two phases: without AIS (Period 1: January 1, 2020 - June 30, 2020) and with AIS (Period 2: January 1, 2021 - June 30, 2021).

Results:

Among 3720 patients (1780 in Period 1, 1940 in Period 2), the discrepancy rate decreased by 17% (p = 0.04) after AIS implementation. Clinically relevant discrepancies showed no significant change (-1.8%, p = 0.99). The mean length of stay in the ED was reduced by 9 minutes (p = 0.03), and expert consultation rates decreased by 1% (p = 0.38).

Conclusion:

AIS implementation reduced the overall discrepancy rate and slightly decreased ED length of stay, although its impact on clinically relevant discrepancies remains inconclusive.

BoneView

BoneView, our first clinical AI application, has become a global bone trauma X-ray interpretation standard, recognized for its scientific excellence. It pinpoints fractures, effusions, dislocations, and bone lesions efficiently. Recognized for its scientific rigor with publications in top-tier peer-reviewed journals, its clinical study won the prestigious 2022 Alexander Margulis Award for scientific excellence.

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Effectiveness of an Artificial Intelligence Software for Limb Radiographic Fracture Recognition in an Emergency Department

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