Ocular diseases present a significant public health concern globally, warranting precise and
efficient diagnostic methodologies. This research aims to develop an approach for …

Ocular diseases pose significant challenges in timely diagnosis and effective treatment.
Deep learning has emerged as a promising technique in medical image analysis, offering …

In response to the evolving landscape of healthcare technology this study addresses the
need for automated diagnostic tools in the field of ophthalmology. By utilizing deep learning …

Currently millions of individuals worldwide are suffering from ocular diseases. Diagnosis of
ocular diseases by conventional methods is challenging, labor-intensive and prone to …

Ophthalmic disorders represent a major global health problem leading to visual impairment
and even blindness if not detected and treated early. Deep learning is a popular approach …

It can be challenging for doctors to identify eye disorders early enough using fundus
pictures. Diagnosing ocular illnesses by hand is time-consuming, error-prone, and …

One of the most challenging tasks for ophthalmologists is early screening and diagnosis of
ocular diseases from fundus images. However, manual diagnosis of ocular diseases is …

Studies show that at least 2.2 billion people in the world have some kind of visual
impairment or blindness. The prevalence of conditions progressing into preventable …

Computer-aided diagnostic systems provide decision support for the early and accessible
detection of ocular diseases. While predictive models exist for certain common diseases in …

Our eyes are fundamental part of our daily lives, enabling us to engage and interact with the
surroundings. Our eyes serve as vital sensory organs, providing us with a wealth of …