The rapid advancement of computational infrastructure has led to unprecedented growth in
machine learning, deep learning, and computer vision, fundamentally transforming the …

Aim To construct predictive models of diabetes complications (DCs) by big data machine
learning, based on electronic medical records. Methods Six groups of DCs were considered …

It is well established that the retina provides insights beyond the eye. Through observation of
retinal microvascular changes, studies have shown that the retina contains information …

Artificial intelligence (AI) has expanded by finding applications in medical diagnosis for
clinical support systems [1]. The use of AI in ophthalmology is drawing enormous interest in …

Diabetic retinopathy (DR) and diabetic macular edema (DME) are the major causes of
permanent blindness in the working-age population. Deep learning methods have been …

Diabetes mellitus (DM) predisposes patients to vascular complications. Retinal images and
vasculature reflect the body's micro-and macrovascular health. They can be used to …

Purpose To assess the capabilities of Chat Generative Pre-trained Transformer (ChatGPT)
and Vertex AI in executing code-free preprocessing, training machine learning (ML) models …

Fundus images are an essential basis for diagnosing ocular diseases, and using
convolutional neural networks has shown promising results in achieving accurate fundus …

Age-related macular degeneration (AMD) is a typical fundus disease that affects the central
vision of elderly people. It causes difficulties in everyday activities such as reading and …

In this article, the development of a computer system for high-tech medical uses in
ophthalmology is proposed. An overview of the main methods and algorithms that formed …