Retrospective Study Comparing Radiologist Diagnostic Performance Versus Artificial Intelligence (AI) for Hip Fracture Suspicion in Elderly Patients
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 1,000
- 试验地点
- 1
- 主要终点
- Detection rate of femoral neck fracture
研究概览
简要总结
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 60 Years 至 —(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- 未提供
排除标准
- 未提供
结局指标
主要结局
Detection rate of femoral neck fracture
时间窗: 1 day
Detection rate of femoral neck fracture
次要结局
- Detection rate of other hip fracture(1 day)
