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临床试验/NCT04678375
NCT04678375已完成不适用

Classification of Retinal Diseases by Artificial Intelligence

Beijing Tongren Hospital1 个研究点 分布在 1 个国家目标入组 1,000,000 人开始时间: 2018年6月1日最近更新:
适应症

试验速览

阶段
不适用
状态
已完成
发起方
入组人数
1,000,000
试验地点
1
主要终点
F1 score

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 from fundus photography. The effectiveness and accuracy of this algorithm was 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. The effectiveness and accuracy of this algorithm was 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
Retrospective

入排标准

年龄范围
18 Years 至 80 Years(Adult, Older Adult)
性别
All
接受健康志愿者

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

F1 score

时间窗: 1 week

We used F1 score to examine the ability of this artificial intelligence algorism recognition and classification of retinal diseases.

Area under curve

时间窗: 1 week

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.

Sensitivity and specificity

时间窗: 1 week

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 week

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

  • Systemic biomarkers and diseases(1 week)

研究者

发起方
Beijing Tongren Hospital
申办方类型
Other
责任方
Sponsor

研究点 (1)

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