In France, femoral neck fracture is mainly detected with interpretation of pelvis/hip X-ray imaging (French Health Authority recommandation).

However, up to 10% of fractures are not identified or misdiagnosed, especially in patients admitted to the emergency department.

Indeed, radiologists may be subject to excessive work, wich cause the risk of inaccurate on X-rays diagnosis.

The Artificial intelligence (AI) begins study the detection of fratures on medical imaging.

In this retropective study, this technology developed by GLEAMER company is tested to evaluate the detection rate of hip fracture and specifically femoral neck fracture, compared to the radiologist diagnostic, in eldery patients admitted in emergency department.

AI could optimize the diagnostic performance of radiologists (increase of confidence level) and improve the efficiency of suspected fractures sorting from emergency department.

Inclusion criteria:

• Patients aged 60 and older
• Minor trauma
• Admitted in emergency department for painful hip/fonctional impotence after minor trauma
• Takes at least a hip radiography

Exclusion criteria:

• Painful before the minor trauma
• Important trauma

Patients aged 60 and older, admitted to emergency department for painful hip/fonctional impotence after minor trauma.

Patients take at least a hip radiography

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