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Pivotal Trial for an Automated AI-based System for Detection of Diabetic Retinopathy

Digital Diagnostics, Inc. · NCT07844317

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Opens the official ClinicalTrials.gov record, with the study team’s contacts. Bored Studies doesn’t enroll anyone.

Key facts

Compensation
Not posted. Ask the study team before screening.
Who can join
Ages 22+ · All sexes
Healthy volunteers
Accepted
Study type
Observational
Target enrollment
800
US sites recruiting
1
Study start
August 24, 2026
Record last updated
September 28, 2026

Status re-checked against ClinicalTrials.gov within the last 12 hours.

What the study is about

Assessment of an autonomous AI system for diabetic retinopathy detection in adults with diabetes using retinal imaging.

Being studied: SaMD intended for the detection of diabetic retinopathy in adults with diabetes.; An AI/ML-based Software as a Medical Device (SaMD) for the automated detection of diabetic retinopathy in adults with diabetes.

Conditions: Diabetic Retinopathy (DR)

Eligibility criteria

Copied from the official record. The study team makes the final decision at screening.

Show full criteria

Inclusion Criteria

  • 22 years of age or older
  • Diagnosis of DM
  • Ability to understand and willing to sign a written ICF

Exclusion Criteria

Participants may be excluded if they have significant ocular conditions or prior ocular treatments that could interfere with retinal imaging or study assessments; are currently participating in another interventional ophthalmic clinical trial; have medical conditions that may affect study participation or data interpretation; are pregnant; or have contraindications to study-related imaging procedures.

Recruiting US locations

  • Rovia Site Network

    Jacksonville, FL 32216

    Site contact: Regional Director of Operations · 904-735-5466 · margot.wrenn@roviaclinical.com

Study contacts (from the official record)

  • Audrey Singh Singh · 7633702127 · singh@digitaldiagnostics.com
All diabetes studies in Florida →
Pivotal Trial for an Automated AI-based System for Detection of… (NCT07844317) | Bored Studies