From subtle breaks to missed diagnoses: Real-world evaluation of an artificial intelligence fracture detection tool

doi:10.5312/wjo.v17.i4.113710

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World Journal of Orthopedics

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2218-5836

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Retrospective Cohort Study

Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Orthop. Apr 18, 2026; 17(4): 113710
Published online Apr 18, 2026. doi: 10.5312/wjo.v17.i4.113710

Table 2 Clinical outcomes of false positive and false negative cases, n (%)

Outcome category	False negatives	False positives	Total
Outpatient/fracture clinic follow-up	33 (61.1)	31 (53.4)	64 (57.1)
CT/MRI performed	8 (14.8)	8 (13.8)	16 (14.3)
ED discharge/conservative management	10 (18.5)	9 (15.5)	19 (17.0)
Admitted	3 (5.6)	6 (10.3)	9 (8.0)
Total	54 (100)	58 (100)	112 (100)

CT: Computed tomography; MRI: Magnetic resonance imaging; ED: Emergency department.

Full Size Table

Citation: Al Hajaj SW, Soliman K, Zafar M, Garnham C, Al Hajaj D, Elshafie O, Alsswah A, Elwan MH. From subtle breaks to missed diagnoses: Real-world evaluation of an artificial intelligence fracture detection tool. World J Orthop 2026; 17(4): 113710
URL: https://www.wjgnet.com/2218-5836/full/v17/i4/113710.htm
DOI: https://dx.doi.org/10.5312/wjo.v17.i4.113710

Al Hajaj SW, Soliman K, Zafar M, Garnham C, Al Hajaj D, Elshafie O, Alsswah A, Elwan MH. From subtle breaks to missed diagnoses: Real-world evaluation of an artificial intelligence fracture detection tool. World J Orthop 2026; 17(4): 113710 [DOI: 10.5312/wjo.v17.i4.113710]

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