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NCT07844317From ClinicalTrials.govRecruiting

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

A Multicenter, Prospective Clinical Trial to Evaluate the Safety and Efficacy of an Automated System for Detecting Diabetic Retinopathy Using a Fundus Camera

  • Diabetic Retinopathy (DR)

At a glance

Phase
Phase not stated
Study type
Observational
Sponsor
Digital Diagnostics, Inc.
Enrolment target
800
Started
24 August 2026
Main results due
30 May 2027
Study sites
1
Registry updated
28 September 2026

Can you take part?

  • Aged 22 years and over.
  • Open to any sex.
  • Healthy volunteers can take part.

These are the headline rules only. Every study has a longer list, and whether you are eligible is decided by the research team at the site — never by this page.

Read the full eligibility 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.

What this study is about

In the sponsor’s own words, from the registry.

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

Study sites(1)

  • Rovia Site Network

    Jacksonville, Florida, United States

    Recruiting

Showing 1 of 1 sites. 1 of the 1 site on this study is recruiting right now — a site can stop enrolling while the study as a whole is still open.

Source: ClinicalTrials.gov record NCT07844317. Trialion does not run this study, is not paid to refer anyone to it, and cannot enrol you. Eligibility is always decided by the research team at the site.

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