In recent years, there has been an unprecedented growth in computer vision and deep
learning implementation owing to the exponential rise of computation infrastructure. The …

Cataracts are the leading cause of visual impairment and blindness globally. Over the years,
researchers have achieved significant progress in developing state-of-the-art machine …

Aim: To design an automated glaucoma detection system for early detection of glaucoma
using fundus images. Background: Glaucoma is a serious eye problem that can cause vision …

Medical images are helpful for the diagnosis, treatment, and evaluation of diseases. Precise
medical image segmentation improves diagnosis and decision-making, aiding intelligent …

Statistics show that an estimated 64 million people worldwide suffer from glaucoma. To aid
in the detection of this disease, this paper presents a new public dataset containing eye …

Diabetic Retinopathy (DR) is the major cause of blindness, which seriously threatens the
world's vision health. Limited medical resources make early diagnosis and a large-scale …

In epidemiology, a risk factor is a variable associated with increased disease risk.
Understanding the role of risk factors is significant for developing a strategy to improve …

Advances in computing and AI technology have promoted the development of connected
health systems, indirectly influencing approaches to cataract treatment. In addition, thanks to …

Artificial intelligence-based medical image analysis promises an efficient and reliable
diagnosis in today's healthcare. Traditional approaches for cataract screening by medical …

Anticipatory monitoring of diabetic retinal (DR) disease is crucial in preventing vision loss
and blindness, making it a leading cause of worldwide vision impairment. In this study, we …