Retrospective Study Comparing Radiologist Diagnostic Performance Versus Artificial Intelligence (AI) for Hip Fracture Suspicion in Elderly Patients
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Painful Hip
- Sponsor
- University Hospital, Montpellier
- Enrollment
- 1000
- Locations
- 1
- Primary Endpoint
- Detection rate of femoral neck fracture
- Status
- Completed
- Last Updated
- 4 years ago
Overview
Brief Summary
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.
Investigators
Eligibility Criteria
Inclusion Criteria
- Not provided
Exclusion Criteria
- Not provided
Outcomes
Primary Outcomes
Detection rate of femoral neck fracture
Time Frame: 1 day
Detection rate of femoral neck fracture
Secondary Outcomes
- Detection rate of other hip fracture(1 day)