Real-world Application of Using Artificial Intelligence in Diagnosing Retinal Diseases
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 100,000
- 试验地点
- 1
- 主要终点
- Area under curve
研究概览
简要总结
The objective of this study is to apply an artificial intelligence algorithm to diagnose multi-retinal diseases in real-world settings. The effectiveness and accuracy of this algorithm are evaluated by sensitivity, specificity, positive predictive value, negative predictive value, and area under curve.
详细描述
The objective of this study is to apply an artificial intelligence algorithm to diagnose referral diabetes retinopathy, referral age-related macular degeneration, referral possible glaucoma, pathological myopia, retinal vein occlusion, macular hole, macular epiretinal membrane, hypertensive retinopathy, myelinated fibers, retinitis pigmentosa and other retinal lesions from fundus photography. tic 45-degree fundus cameras, trained operators took binocular fundus photography on participants. Operators were then asked to identify gradable images and unload for algorithm diagnosis. The effectiveness and accuracy of this algorithm are evaluated by sensitivity, specificity, positive predictive value, negative predictive value, area under curve, and F1 score.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 1 Year 至 100 Years（Child, Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •fundus photography around 45° field which covers optic disc and macula
- •complete identification information
排除标准
- •insufficient information for diagnosis
结局指标
主要结局
Area under curve
时间窗: 1 month
We used the receiver operating characteristic (ROC) curve and area under curve to examine the ability of this artificial intelligence algorism recognition and classification of retinal diseases.
F1 score
时间窗: 1 month
We used F1 score to examine the ability of this artificial intelligence algorism recognition and classification of retinal diseases.
Sensitivity and specificity
时间窗: 1 month
We used sensitivity and specificity to examine the ability of this artificial intelligence algorism recognition and classification of retinal diseases.
Positive predictive value, negative predictive value
时间窗: 1 month
We used positive predictive value and negative predictive value to examine the ability of this artificial intelligence algorism recognition and classification of retinal diseases.
次要结局
未报告次要终点
研究者
Wenbin Wei
Prof
Beijing Tongren Hospital