Diabetic Retinopathy Assessment through Multitask Learning Approach on Heterogeneous Fundus Image Datasets.

ABSTRACT:

Objective

To develop and validate an artificial intelligence (AI)-based system, Diabetic Retinopathy Analysis Model Assistant (DRAMA), for diagnosing diabetic retinopathy (DR) across multisource heterogeneous datasets and aimed at improving the diagnostic accuracy and efficiency.

Design

This was a cross-sectional study conducted at Zhejiang University Eye Hospital and approved by the ethics committee.

Subjects

The study included 1500 retinal images from 957 participants aged 18 to 83 years. The dataset was divided into 3 subdatasets: color fundus photography, ultra-widefield imaging, and portable fundus camera. Images were annotated by 3 experienced ophthalmologists.

Methods

The AI system was built using EfficientNet-B2, pretrained on the ImageNet dataset. It p

SUBMITTER: Wu H 

PROVIDER: S-EPMC12167062 | biostudies-literature | 2025 Sep-Oct

REPOSITORIES: biostudies-literature