Associated factors of diabetic retinopathy by artificial intelligence evaluation of fundus images in Japan.

ABSTRACT: This cross-sectional study aimed to investigate the promoting and inhibitory factors of diabetic retinopathy (DR) according to diabetes mellitus (DM) stage using standardized evaluation of fundus images by artificial intelligence (AI). A total of 30,167 participants underwent blood and fundus examinations at a health screening facility in Japan (2015-2016). Fundus photographs were screened by the AI software, RetCAD and DR scores (DRSs) were quantified. The presence of DR was determined by setting two cut-off values prioritizing sensitivity or specificity. DM was defined as four stages (no DM: DM0; advanced DM: DM3) based on treatment history and hemoglobin A1c (HbA1c) levels. Associated factors of DR were identified using logistic regression analysis. For cutoff values, multivariate analy

SUBMITTER: Komatsu K 

PROVIDER: S-EPMC10643360 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature