Latest AI and machine learning research in glaucoma for healthcare professionals.
Glaucoma is an incurable ophthalmic disease that damages the optic nerve, leads to vision loss, and ranks among the leading causes of blindness worldwide. Diagnosing glaucoma typically involves fundus photography, optical coherence tomography (OCT), and visual field testing. However, the high cost of OCT often leads to reliance on fundus photography and visual field testing, both of which exhibi...
Subject of research: is the study of methods for analyzing perimetric images for the diagnosis and control of glaucoma diseases. Objects of research: is a dataset collected on the ophthalmological perimeter with the results of various patient pathologies, since the ophthalmological community is acutely aware of the issue of disease control and import substitution. [5]. Purpose of research: is to...
Structural changes in main retinal blood vessels serve as critical biomarkers for the onset and progression of glaucoma. Identifying these vessels i...
PURPOSE: The purpose of this study was to develop models that predict which patients with glaucoma will progress to require surgery, combining structu...
Glaucomatous optic neuropathy (GON) is a prevalent ocular disease that can lead to irreversible vision loss if not detected early and treated. The t...
Glaucoma is a prevalent eye disease that progresses silently without symptoms. If not detected and treated early, it can cause permanent vision loss...
The Convolutional Neural Network (CNN) has shown impressive performance in image classification because of its strong learning capabilities. However...
The advent of foundation models (FMs) is transforming medical domain. In ophthalmology, RETFound, a retina-specific FM pre-trained sequentially on 1...
The prevalence of ocular illnesses is growing globally, presenting a substantial public health challenge. Early detection and timely intervention ar...
Glaucoma is a leading cause of irreversible blindness worldwide, emphasizing the critical need for early detection and intervention. In this paper, ...
The emergence of artificial intelligence (AI), particularly deep learning (DL), has marked a new era in the realm of ophthalmology, offering transfo...
Retinal vascular morphology is crucial for diagnosing diseases such as diabetes, glaucoma, and hypertension, making accurate segmentation of retinal...
PURPOSE: The integration of artificial intelligence (AI), particularly deep learning (DL), with optical coherence tomography (OCT) offers significant ...
Diffusion magnetic resonance imaging is a non-invasive neuroimaging technique that enables in vivo evaluation of white matter microstructure, providin...
Accurate retinal Microvascular segmentation demands a balanced combination of anatomical fidelity and hemodynamic relevance. However, existing methods...
To develop an equitable deep learning model with knowledge distillation to enhance the demographic equity in glaucoma progression prediction. We devel...
This study evaluates the diagnostic performance of several AI models, including Deepseek, in diagnosing corneal diseases, glaucoma, and neuroâ–¡ophthalm...
Glaucoma is a leading cause of irreversible blindness worldwide, with early diagnosis often hindered by subtle symptomatology and the lack of comprehe...
Real-world ocular imaging datasets are essential for advancing research in artificial intelligence (AI), autonomous disease screening, and clinical de...
Glaucoma is increasingly recognized as a neurodegenerative condition involving both retinal and central nervous system structures. Here, we present an...