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ACTIVE NOT RECRUITING
NCT03694145

Predicting Diabetic Retinopathy From Risk Factor Data and Digital Retinal Images

Sponsor: Charles Drew University of Medicine and Science

View on ClinicalTrials.gov

Summary

The objective of this study is to compare the results of a deep learning approach to diabetic retinopathy assessment with results from (1) an in-person examination with an ophthalmologist, and (2) the assessments of optometrists involved in a teleretinal screening program.

Key Details

Gender

All

Age Range

18 Years - Any

Study Type

OBSERVATIONAL

Enrollment

300

Start Date

2018-10-25

Completion Date

2025-07-31

Last Updated

2025-02-14

Healthy Volunteers

No

Interventions

OTHER

In-Person Eye Examination

Dilated in-person eye examination by a board-certified ophthalmologist or retinal fellow.

Locations (3)

Los Angeles Department of Public Health

Los Angeles, California, United States

University of California - Los Angeles

Los Angeles, California, United States

Charles R. Drew University of Medicine and Science

Los Angeles, California, United States