Accuracy of Integrated Artificial Intelligence Grading Using Handheld Retinal Imaging in a Community Diabetic Eye Screening Program.

ABSTRACT:

Purpose

To evaluate mydriatic handheld retinal imaging performance assessed by point-of-care (POC) artificial intelligence (AI) as compared with retinal image graders at a centralized reading center (RC) in identifying diabetic retinopathy (DR) and diabetic macular edema (DME).

Design

Prospective, comparative study.

Subjects

Five thousand five hundred eighty-five eyes from 2793 adult patients with diabetes.

Methods

Point-of-care AI assessment of disc and macular handheld retinal images was compared with RC evaluation of validated 5-field handheld retinal images (disc, macula, superior, inferior, and temporal) in identifying referable DR (refDR; defined as moderate nonproliferative DR [NPDR], or worse, or any level of DME) and vision-threatening DR (vtDR; define

SUBMITTER: Salongcay RP 

PROVIDER: S-EPMC10838904 | biostudies-literature | 2024 May-Jun

REPOSITORIES: biostudies-literature