Artificial Intelligence System for Assessing Image Quality of Slit-Lamp Images and Its Effects on Diagnosis: A Clinical Trial
试验速览
- 阶段
- 不适用
- 发起方
- 入组人数
- 300
- 试验地点
- 1
- 主要终点
- Performance of artificial intelligence system for distinguish between good image quality and poor image quality
研究概览
简要总结
Slit-lamp images are widely used in ophthalmology for the detection of cataract, keratopathy and other anterior segment disorders. In real-world practice, the quality of slit-lamp images can be unacceptable, which can undermine diagnostic accuracy and efficiency. Here, the researchers established and validated an artificial intelligence system to achieve automatic quality assessment of slit-lamp images upon capture. This system can also provide guidance to photographers according to the reasons for low quality.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Patients should be aware of the contents and signed for the informed consent.
排除标准
- •Patients who cannot cooperate with a photographer such as some paralytics, the patients with dementia and severe psychopaths.
- •Patients who do not agree to sign informed consent.
结局指标
主要结局
Performance of artificial intelligence system for distinguish between good image quality and poor image quality
时间窗: 3 months
Area under the receiver operating characteristic curves, sensitivity, specificity, positive and negative predictive values,accuracy
次要结局
- The comparison of the performance for previous artificial intelligence diagnostic system with slit-lamp images of different image quality(3 months)
研究者
Haotian Lin
Clinical Professor
Sun Yat-sen University