Back to search results

Observational Study of AI for Early Diagnosis of Diabetic Retinopathy

This study is looking at how well an artificial intelligence (AI) software called iPredict-DR can find early signs of diabetic retinopathy (DR) in people with diabetes. DR is a common eye problem for people with diabetes that can lead to blindness if not caught early. Currently, eye doctors screen for DR, but this can be time-consuming and expensive. This study wants to see if iPredict-DR can help diagnose DR accurately using eye photos, similar to how human experts do. You may be able to join if you are at least 22 years old, have diabetes (A1C level of 6.5 or higher), and are willing to follow study procedures.

Study design
This is an observational study that plans to include 922 participants. It will compare the AI software's results to those of human experts.
What's involved
You would need to attend clinic visits and understand the study procedures.
Compensation
Not stated in the trial record.
Follow-up
The accuracy of the software will be measured at 1-year or 2-year intervals.

AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.

NCT07151001

Pivotal Trial of Automated Artificial Intelligence (AI) Based System for Early Diagnosis of Diabetic Retinopathy

Recruiting
Not specifiedAges 22+Observational
iHealthScreen Inc
~922 participants
Updated 2025-09-02 on ClinicalTrials.gov
What's tested:No intervention

At a glance

Recruiting sites
1 of 1 listed site is recruiting right now
RecruitingSuspended, closed, or not yet open
What they're measuring
mtmDR detected (Referable DR) OR mtmDR not detected (non-referable DR)
Measured over 1-year or 2-year
+1 more outcome measured

Conditions

Diabetes
Diabetic Retinopathy

Explore related trials

Diabetes Mellitus

Where it's being run

1 sites across 1 states
New York1

Study leadership

  • Alauddin Bhuiyan, PhD · PRINCIPAL_INVESTIGATOR · iHealthScreen Inc

Who to contact

Alauddin Bhuiyan
[email protected]
718-926-9000
Email the study team

Opens a ready-to-send draft in your own email app — review before sending.

Do you actually qualify for this trial?

Add a private profile and we'll compare every criterion below against your situation — and tell you which ones are met, uncertain, or excluding.

Check eligibility for this trial ~2 min · HIPAA-protected · delete anytime
Eligibility criteria

Inclusion

Age of Subjects: Patients ≥ 22 years of age.
Gender of Subjects: Both males and females will be invited to participate.
Subjects with diabetes (A1C level ≥ 6.5).
Subjects must be willing and are able to comply with clinic visit, understand the study-related procedures/provisions, and provide signed informed consent.

Exclusion

Unable to understand the study, Our unable to or unwilling to sign the informed consent
Previously diagnosed with macular edema, any form of diabetic retinopathy, radiation retinopathy, or retinal vein occlusion
participants who are experiencing persistent vision loss, blurred vision, or other vision problems that should be evaluated by an eye care provider
subjects whose retinal images were used in training, validating, or developing the device
Currently participating in another investigational eye study or actively receiving investigational product for DR or DME.
A condition that, in the opinion of the investigator, would preclude participation in the study;
Contraindicated for imaging by fundus imaging systems used in the study because of hypersensitivity to light, recently underwent photodynamic therapy, or was taking medication that causes photosensitivity.

What this trial measures

  • mtmDR detected (Referable DR) OR mtmDR not detected (non-referable DR)1-year or 2-year

    Sensitivity and specificity of identification of referable and non-referable DR for early diagnosis of DR using the iPredict-DR's AI-based DR screening software utilizing color fundus imaging. iPredict-DR can detect non-referable DR (normal retina or mild DR) and referable DR (moderate or severe DR including moderate non-proliferative, proliferative DR and diabetic macular edema) at a similar level of expert ophthalmologists. For this, the healthcare workers will be taking the disc and macula center 45-degree field view images using DRSPlus camera (from iCare Inc.). The output of AI model and ground truth (produced by graders from reading centers) will be compared for image level and subject level accuracy measurements. The worst eye will be considered to define a subject's referability or non-referability to an ophthalmologist. Using the ground truth/gold standard, the sensitivity, specificity, precision, recall, accuracy, F-measure, positive predictive value and negative predictive

  • The accuracy of the iPredict-DR software developed by iHealthScreen system in early diagnosis of DR using color retinal photos vs. that of human expert graders1-year or 2-year

    The accuracy of the iPredict-DR software developed by iHealthScreen system in early diagnosis of DR using color retinal photos vs. that of human expert graders for DR. Performance thresholds were defined at 80.0% for sensitivity and 80.0% for specificity