Deep learning for detecting visually impaired cataracts using fundus images.

To develop a visual function-based deep learning system (DLS) using fundus images to screen for visually impaired cataracts. A total of 8,395 fundus images (5,245 subjects) with corresponding visual function parameters collected from three clinical centers were used to develop and evaluate a DLS for classifying non-cataracts, mild cataracts, and visually impaired cataracts. Three deep learning algorithms (DenseNet121, Inception V3, and ResNet50) were leveraged to train models to obtain the best one for the system.