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Artificial-Intelligence-based Early Detection of Diabetic Retinopathy (FUNDUS AI) | Clinical Trials | Clareo Health

ENROLLING_BY_INVITATION

Artificial-Intelligence-based Early Detection of Diabetic Retinopathy (FUNDUS AI)

Künstliche Intelligenz (KI)-gestützte Früherkennung Der Diabetischen Retinopathie (FUNDUS-KI)

NCT07378891•University Hospital Tuebingen

View on ClinicalTrials.gov

Summary

Examination of individuals with prediabetes and established diabetes for early signs of diabetic retinopathy.

Detailed Description

Fundus images are acquired and analyzed using an AI algorithm. The fundus images are captured using two devices: a stationary fundus camera (CenterVue DRSplus) and the Optomed Aurora IQ handheld fundus camera. Retinal images are examined using AI-based image analysis.

Eligibility

Age

18 - 80 years

Sex

ALL

Healthy Volunteers

Inclusion Criteria

•Voluntary adults
•Aged between 18 and 80 years
•Understanding of the study explanations and instructions
•Prediabetes (defined by elevated fasting glucose 100-125 mg/dL and/or 2-hour glucose in the oral glucose tolerance test of 140-199 mg/dL and/or HbA1c of 5.7-6.4%)
•manifest diabetes (all types of diabetes according to Ahlqvist)

Exclusion Criteria

•participants unable to give consent
•Those who do not agree to be informed about incidentally detected pathological findings
•Uncontrolled arterial hypertension (Stage III) despite multiple antihypertensive medications
•Eye diseases that impair the interpretability of the fundus examination

Locations (1)

University Hospital Tuebingen, Dep. Diabetology

Tübingen, Germany

Key Dates

Start Date

December 1, 2025

Primary Completion Date

October 1, 2028

Completion Date

December 15, 2028

Last Updated

February 10, 2026

Enrollment

100

ESTIMATED participants

Conditions

Diabetes (DM)Prediabetes

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PreDiabetes

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Data Source & Attribution

This clinical trial information is sourced from ClinicalTrials.gov, a service of the U.S. National Institutes of Health.

ClinicalTrials.gov last update: February 10, 2026Data synced to Clareo: March 29, 2026

Modifications: This data has been reformatted for display purposes. Eligibility criteria have been parsed into inclusion/exclusion sections. Location data has been geocoded to enable distance-based search. For the authoritative and most current information, please visit ClinicalTrials.gov.

Neither the United States Government nor Clareo Health make any warranties regarding the data. Check ClinicalTrials.gov frequently for updates.

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Artificial-Intelligence-based Early Detection of Diabetic Retinopathy (FUNDUS AI)

Inclusion Criteria

Exclusion Criteria

Pharmacogenetics of the Response to GLP-1 in Mexican-Americans With Prediabetes

Rural Alliance for Diabetes Prevention

Human Immunodeficiency Virus (HIV) Food Insecurities

WatchWell: Simple and Practical Strategies to Reduce the Negative Health Impact of Sedentary Screen Time

Development of an Inclusive Adaptive Treatment Strategy for Weight Loss in People With Prediabetes Using a Sequential Multiple Assignment Randomized Trial

Impact of the New Generation Anti-diabetic Drugs on Diabetic Retinopathy