NCT04678375

Artificial Intelligence for Detecting Retinal Diseases

Classification of Retinal Diseases by Artificial Intelligence

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 1,000,000 (actual)
• Sponsor: Beijing Tongren Hospital · Academic / Other
• Sex: All
• Age: 18 Years – 80 Years
• Healthy volunteers: Accepted

Summary

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.

Detailed description

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.

Conditions

• Artificial Intelligence
• Retinal Diseases

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	Retinal diseases diagnosed by artificial intelligence algorithm	An artificial intelligence algorithm was applied 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.

Timeline

• Start date: 2018-06-01
• Primary completion: 2020-06-30
• Completion: 2020-10-01
• First posted: 2020-12-21
• Last updated: 2021-04-15

Locations

1 site across 1 country: China