Ocular diseases can range in severity, with some being more serious than others. As a
matter of fact, there are several common and severe eye diseases, for instance, glaucoma …

Automated grading of diabetic retinopathy (DR) is an important means for assisting clinical
diagnosis and preventing further retinal damage. However, imbalances and similarities …

The incident light reflected from the cornea is rich in information about the human
surroundings, and these reflected rays are imaged by the camera, which can be used for …

To assess the feasibility of code-free deep learning (CFDL) platforms in the prediction of
binary outcomes from fundus images in ophthalmology, evaluating two distinct online-based …

This study proposes a novel methodology for classifying ocular diseases using
convolutional neural networks (CNNs) and specialized loss functions. The proposed model …

Purpose Crystalline retinopathy is characterized by reflective crystal deposits in the macula
and is caused by various systemic conditions including hereditary, toxic, and embolic …

Background and objective The unique organ that provides vision is eye and there are
various disorders cause visual impairment. Therefore, the identification of eye diseases in …

Deep Learning (DL) has proliferated interest in ocular disease detection in recent years, and
several DL architectures were proposed. DL architectures deploy multiple layers to capture …

The main factor causing irreversible blindness is glaucoma. Early detection greatly reduces
the risk of further vision loss. To address this problem, we developed a domain adaptation …

Automatic diagnosis of various ophthalmic diseases from ocular medical images is vital to
support clinical decisions. Most current methods employ a single imaging modality …