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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT05981950
Other study ID # Real-world RAIDS
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date August 1, 2023
Est. completion date August 1, 2029

Study information

Verified date August 2023
Source Beijing Tongren Hospital
Contact Wenbin Wei, MD
Phone 58269516
Email weiwenbintr@163.cim
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

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.


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. 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.


Recruitment information / eligibility

Status Recruiting
Enrollment 100000
Est. completion date August 1, 2029
Est. primary completion date August 1, 2028
Accepts healthy volunteers
Gender All
Age group 1 Year to 100 Years
Eligibility Inclusion Criteria: - fundus photography around 45° field which covers optic disc and macula - complete identification information Exclusion Criteria: - insufficient information for diagnosis

Study Design


Related Conditions & MeSH terms


Intervention

Diagnostic Test:
artificial intelligence algorithm
Retinal diseases diagnosed by artificial intelligence algorithm

Locations

Country Name City State
China Wen-Bin Wei Beijing Beijing

Sponsors (1)

Lead Sponsor Collaborator
Beijing Tongren Hospital

Country where clinical trial is conducted

China, 

Outcome

Type Measure Description Time frame Safety issue
Primary Area under curve 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. 1 month
Primary Sensitivity and specificity We used sensitivity and specificity to examine the ability of this artificial intelligence algorism recognition and classification of retinal diseases. 1 month
Primary Positive predictive value, negative predictive value We used positive predictive value and negative predictive value to examine the ability of this artificial intelligence algorism recognition and classification of retinal diseases. 1 month
Primary F1 score We used F1 score to examine the ability of this artificial intelligence algorism recognition and classification of retinal diseases. 1 month
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