Ocular diseases can lead to irreversible vision impairment if not treated timely. Various
imaging techniques have been developed to aid in the detection of ocular diseases …

Early detection and treatment of visual impairment diseases are critical and integral to
combating avoidable blindness. To enable this, artificial intelligence–based disease …

Purpose: To develop and validate an artificial intelligence framework for identifying multiple
retinal lesions at image level and performing an explainable macular disease diagnosis at …

Glaucoma, a disease characterized by the progressive and irreversible defect of the visual
field, requires a lifelong course of treatment once it is confirmed, which highlights the …

Deep neural networks (DNNs) have been widely applied to the automatic analysis of
medical images for disease diagnosis and to help human experts by efficiently processing …

Abstract Optical Coherence Tomography (OCT) is a novel and effective screening tool for
ophthalmic examination. Since collecting OCT images is relatively more expensive than …

While accurate disease prediction from retinal fundus images is critical, collecting large
amounts of high quality labeled training data to build such supervised models is difficult …

To demonstrate the identification of corneal diseases using a novel deep learning algorithm.
A novel hierarchical deep learning network, which is composed of a family of multi-task multi …

Automatic clinical diagnosis of retinal diseases has emerged as a promising approach to
facilitate discovery in areas with limited access to specialists. Based on the fact that fundus …

With recent advancements in machine learning, especially in deep learning, the prediction
of eye diseases based on fundus photography using deep convolutional neural networks …