Comparing Artificial Intelligence for Assisted Diagnosis of Diabetic Retinopathy

A Comparative Analysis of the Diagnostic Outcomes of Artificial Intelligence-assisted Fundus Photography for Diabetic Retinopathy and Diabetic Macular Edema Versus Other Imaging Devices in Ophthalmology: A Controlled Trial

Status

Not yet recruiting

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT06423274

Enrollment

1000

Registered

2024-05-21

Start date

2024-07-10

Completion date

2025-12-31

Last updated

2024-07-09

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Diabetic Retinopathy, Diabetic Macular Edema

Keywords

diabetic retinopathy, diabetic macular edema, artificial intelligence

Brief summary

Detailed description

This study plans to compare the accuracy of artificial intelligence (AI)-assisted fundus images with other ophthalmic devices such as optical coherence tomography (OCT) and fundus fluorescence angiography (FFA) in the diagnosis of diabetic retinopathy and diabetic macular edema. This study was conducted as a prospective study. Participants meeting eligibility criteria will be recruited from sites staffed by trained photographers. After assessing eligibility and obtaining informed consent, fundus photographs will be taken using a non-dilated fundus camera. And optical coherence tomography or fundus fluorescence angiography will be performed.

Interventions

DIAGNOSTIC_TESTfundus photography

using artificial intelligence to identify diabetic retinopathy using fundus photography

DIAGNOSTIC_TESToptical coherence tomography

detect diabetic retinopathy and diabetic macular edema by optical coherence tomography

DIAGNOSTIC_TESTfundus fluorescence angiography

detect diabetic retinopathy by fundus fluorescence angiography

Study design

Observational model

COHORT

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to 90 Years

Healthy volunteers

Yes

Inclusion criteria

1. Diagnostic for diabetes: Type 1 diabetes of a lest 5 years of evolution; or Type 2 diabetes; 2. Obtaining informed consent; 3. Patient age 18 or above.

Exclusion criteria

1. Patients under 18 years of age; 2. Failure to Obtain informed consent; 3. Presence of other retinal diseases; 4. A patient who has already undergone the treatment.

Design outcomes

Primary

Measure	Time frame	Description
The accuracy	Baseline-Month 12	Detection of DR accuracy using fundus photography, optical coherence tomography, and fundus fluorescence angiography

Secondary

Measure	Time frame	Description
The accuracy	Baseline-Month 12	Detection of DME accuracy using fundus photography, optical coherence tomography, and fundus fluorescence angiography

Countries

China

Contacts

Primary ContactHongkang Wu, MMS

wuhongkang@zju.edu.cn+8618969978676

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026