Improving diabetic retinopathy screening using artificial intelligence: design, evaluation and before-and-after study of a custom development.

ABSTRACT:

Background

The worst outcomes of diabetic retinopathy (DR) can be prevented by implementing DR screening programs assisted by AI. At the University Hospital of Navarre (HUN), Spain, general practitioners (GPs) grade fundus images in an ongoing DR screening program, referring to a second screening level (ophthalmologist) target patients.

Methods

After collecting their requirements, HUN decided to develop a custom AI tool, called NaIA-RD, to assist their GPs in DR screening. This paper introduces NaIA-RD, details its implementation, and highlights its unique combination of DR and retinal image quality grading in a single system. Its impact is measured in an unprecedented before-and-after study that compares 19,828 patients screened before NaIA-RD's implementation and 22,962 pa

SUBMITTER: Pinto I 

PROVIDER: S-EPMC12222278 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature