Glaucoma

Identification of diagnostic biomarkers and dissecting immune microenvironment with crosstalk genes in the POAG and COVID-19 nexus.

An underlying association between primary open-angle glaucoma (POAG) and COVID-19 has been hypothesized, but the causal link and shared mechanisms remain unclear. This study integrates epidemiological and bioinformatics approaches to investigate their relationship, aiming to identify common molecular pathways and validate clinical correlations. Epidemiological data from 3,015 participants in the C...

D-optimal candexch algorithm-enhanced machine learning UV-spectrophotometry for five-analyte determination in novel anti-glaucoma formulations and ocular fluids: four-color sustainability framework with NQS assessment and UN-SDG integration.

The novel anti-glaucoma ophthalmic preparation containing latanoprost, netarsudil, and benzalkonium chloride has posed a significant challenge due to its complexity and the lack of environmentally sustainable quantification methods, with only a single published method available for its quantification that lacks environmental consideration. This study aims to address this crucial gap by presenting ...

A three-tier AI solution for equitable glaucoma diagnosis across China's hierarchical healthcare system.

Artificial intelligence (AI) offers a solution to glaucoma care inequities driven by uneven resource distribution, but its real-world implementation r...

GAINSeq: glaucoma pre-symptomatic detection using machine learning models driven by next-generation sequencing data.

Congenital glaucoma, a complex and diverse condition, presents considerable difficulties in its identification and categorization. This research used ...

Interpretable longitudinal glaucoma visual field estimation deep learning system from fundus images and clinical narratives.

Glaucoma is a globally prevalent disease that leads irreversible blindness. The visual field (VF) examination is important but time-consuming for visu...

Analysis of 2-dimensional regional differences in the peripapillary scleral fibroblast cytoskeleton of normotensive and hypertensive mouse eyes.

These studies aimed to study the mechanisms of glaucomatous peripapillary scleral (PPS) remodeling by investigating IOP-induced changes in fibroblast ...

Prospective pragmatic trial of automated retinal photography and AI glaucoma screening in Australian primary care.

There are no prospective clinical studies evaluating artificial intelligence implementation for glaucoma detection in real-world settings. We develope...

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UNLABELLED: Early detection of glaucoma represents a vital factor in securing vision while the disease retains its position as one of the central caus...

Screening of Glaucoma in High-Risk Minority Populations.

PRECIS: This chapter reviews the current recommendations on screening for open angle glaucoma in Black and Hispanic populations. Strategies for increa...

Predicting Retinal Nerve Fiber Layer Thickness From Ocular Hypertension Treatment Study Optic Disc Photographs.

IMPORTANCE: Deep learning predictions of retinal nerve fiber layer (RNFL) thickness derived from optic disc photographs may help to determine risk for...

Evaluating real-world performance of an automated offline glaucoma AI on a smartphone fundus camera across glaucoma severity stages.

PURPOSE: Leveraging an artificial intelligence system (AI) for glaucoma screening can mitigate the current challenges and provide prompt detection and...

Topo-CNN: Retinal Image Analysis with Topological Deep Learning.

The analysis of fundus images is vital for early detection of retinal diseases such as diabetic retinopathy (DR), glaucoma, and age-related macular de...

Macular pigment optical density and measurement technology based on artificial intelligence: a narrative review.

Macular pigment (MP) is a crucial pigment in the macular region. It plays an important role in filtering blue light, and exhibits anti-inflammatory an...

Artificial intelligence for glaucoma.

This is a protocol for a Cochrane Review (diagnostic). The objectives are as follows: To determine the accuracy of artificial intelligence (AI) algori...

Retinal Vessel Traits and Age-Related Eye Disease in the Canadian Longitudinal Study on Aging.

BACKGROUND: To cross-sectionally and longitudinally examine whether retinal vessel traits are associated with glaucoma-related outcomes (glaucoma, cup...

Unsophisticated AI coaching does not improve performance on symptom and performance validity tests in a Romanian sample of experimental feigners.

The present study aimed to investigate the ability of symptom and performance validity indicators to detect experimental feigning with symptom-coachin...

Glaucoformer: Dual-domain Global Transformer Network for Generalized Glaucoma Stage Classification.

Classification of glaucoma stages remains challenging due to substantial inter-stage similarities, the presence of irrelevant features, and subtle les...

Ophthalmic Image Synthesis and Analysis with Generative Adversarial Network Artificial Intelligence.

Generative adversarial networks (GANs), introduced by Ian Goodfellow in 2014, have revolutionized adversarial machine learning, particularly in data s...

An Artificial Intelligence Method for Phenotyping of OCT-Derived Thickness Maps Using Unsupervised and Self-supervised Deep Learning.

The objective of this study is to enhance the understanding of ophthalmic disease physiology and genetic architecture through the analysis of optical ...

Analysis of Standard Automated Visual Field Tests in Glaucoma and the Role of Facial Contour.

PRCIS: Using a CNN-enhanced platform, 60-4 visual fields identified peripheral glaucomatous defects missed by central testing in mild cases; facial co...