Autonomous Artificial Intelligence in Diabetic Retinopathy: From Algorithm to Clinical Application.
Roomasa Channa, Risa Wolf, Michael D Abramoff
https://pubmed.ncbi.nlm.nih.gov/32126819Actively Recruiting
Phase Not Applicable
Age: 8Years - 21Years
All Genders
ID05463289
Implementing Digital Retinal Exams Into Comprehensive Pediatric Diabetes Care Using Autonomous AI
Led by Johns Hopkins University · Updated on 2026-03-27
500
Participants Needed
1
Research Sites
N/A
Total Duration
On this page
Sponsors
J
Johns Hopkins University
Lead Sponsor
N
National Eye Institute (NEI)
Collaborating Sponsor
AI-Summary
What this Trial Is About
Researchers are evaluating whether using a non-mydriatic fundus camera with autonomous artificial intelligence (AI) software at the point of care can increase the number of underserved youth with diabetes who are screened for diabetic retinopathy. The study also aims to assess the accuracy of the AI system in detecting diabetic retinopathy from retinal images in young people aged 8 to 21 with type 1 or type 2 diabetes. Participants will undergo a diabetic eye exam using the autonomous AI software on a non-mydriatic fundus camera, which provides immediate results. Those who test positive for diabetic retinopathy will be referred to an eye care provider for a dilated eye exam. The study includes a group of youth with known diabetic retinopathy to help determine the AI system's diagnostic accuracy compared to standard expert grading. During the study, participants will have their retinal images analyzed by the AI system at the point of care. Researchers will measure the proportion of youth screened for diabetic retinopathy and evaluate how well the AI system's results agree with expert graders. The study will monitor safety and accuracy on the day of the exam and follow participants' outcomes to support the use of AI in pediatric diabetes eye care.
CONDITIONS
Brief Title
ACCESS 2: AI for pediatriC diabetiC Eye examS Study 2
Who Can Participate
Age: 8Years - 21Years
All Genders
Eligibility Criteria
You may qualify if you...
- Meets American Diabetes Association criteria for diabetic retinopathy screening
- Diagnosis of type 1 diabetes for 3 or more years and age 11 or in puberty
- Diagnosis of type 2 diabetes
- Age between 8 and 21 years
- Enriched cohort includes youth aged 8-21 with known diabetic retinopathy
- No time limit on last diabetic eye exam for enriched cohort
You will not qualify if you...
- Known diabetic eye exam in the last 12 months
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
1
2
3
Your Study Journey
Screening
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person)
Surveillance
Duration - Day 1
Participants undergo a point-of-care diabetic retinopathy screening using autonomous AI software which provides immediate results. Those with abnormal results are referred to an eye care provider for further examination.
1 visit (in-person)
Trial Site Locations
Total: 1 location
1
Johns Hopkins Pediatric Diabetes Center
Baltimore, Maryland, United States, 21287
Actively Recruiting
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Research Team
R
Risa M Wolf, MD
A
Alvin Liu, MD
How is the study designed?
Study Type
INTERVENTIONAL
Masking
NONE
Allocation
NA
Model
SINGLE_GROUP
Primary Purpose
SCREENING
Number of Arms
1
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Published Research Related To This Trial
Racial/Ethnic Disparities and Barriers to Diabetic Retinopathy Screening in Youths.
Chrystal G Thomas, Roomasa Channa, Laura Prichett...
https://pubmed.ncbi.nlm.nih.gov/34042939Cost-effectiveness of Autonomous Point-of-Care Diabetic Retinopathy Screening for Pediatric Patients With Diabetes.
Risa M Wolf, Roomasa Channa, Michael D Abramoff...
https://pubmed.ncbi.nlm.nih.gov/32880616The SEE Study: Safety, Efficacy, and Equity of Implementing Autonomous Artificial Intelligence for Diagnosing Diabetic Retinopathy in Youth.
Risa M Wolf, T Y Alvin Liu, Chrystal Thomas...
https://pubmed.ncbi.nlm.nih.gov/33479160Prevalence of diabetic retinopathy in children and adolescents at an urban tertiary eye care center.
Mark Porter, Roomasa Channa, Jessica Wagner...
https://pubmed.ncbi.nlm.nih.gov/32410329