Traumatic emergencies are the primary reason for consultation in emergency departments and standard radiography is the primary imaging exam for osteoarticular trauma. However, with the increase in the number of patients admitted to emergency departments and thus the increased workload for emergency room attendants, Interpretation of radiographs in trauma emergencies is made more difficult, resulting in a high risk of misinterpretation.
The growing presence of artificial intelligence in the medical field, notably through the involvement of diagnostic software on imageries, makes its use more relevant in the aid of the replay of osteoarticular imageries.
A recent meta-analysis of 32 studies evaluating the performance of artificial intelligence in fracture detection found comparable performance between experienced radiologists and AI-based diagnosis. However, these were mainly retrospective studies, and thus more distant from the reality of its use in a care stream such as emergencies.
The objective of this study is therefore to prospectively validate the use of artificial intelligence software during its implementation in an emergency department for patients admitted for a suspicion of osteoarticular trauma.
Major patient
Admitted to the emergency department after trauma less than 48 hours
Patient with an indication on an x-ray of the limbs or/and pelvis
Express patient consent
Polytraumatized patient
X-ray of the corso-lumbar spine, skull, cervical spine (all parts of the body not affected by the intended use of the software)
Pregnant, lactating or parturient patient
Single group
processing the radiography with the "Boneview" software
Diagnostic testall X-Rays will be analysed with and without the software
Change in ER support between X-ray reading without and with artificial intelligence
Compare ER support decisions without and with fracture diagnostic software
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