Deep learning algorithms to detect diabetic kidney disease from retinal photographs in multiethnic populations with diabetes.

ABSTRACT:

Objective

To develop a deep learning algorithm (DLA) to detect diabetic kideny disease (DKD) from retinal photographs of patients with diabetes, and evaluate performance in multiethnic populations.

Materials and methods

We trained 3 models: (1) image-only; (2) risk factor (RF)-only multivariable logistic regression (LR) model adjusted for age, sex, ethnicity, diabetes duration, HbA1c, systolic blood pressure; (3) hybrid multivariable LR model combining RF data and standardized z-scores from image-only model. Data from Singapore Integrated Diabetic Retinopathy Program (SiDRP) were used to develop (6066 participants with diabetes, primary-care-based) and internally validate (5-fold cross-validation) the models. External testing on 2 independent datasets: (1) Singapore Epidemio

SUBMITTER: Betzler BK 

PROVIDER: S-EPMC10654858 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature