Glaucoma

Comparing the Accuracy of 4 Artificial Intelligence Models in PubMed Citation Generation for Glaucoma Research.

PRCIS: DeepSeek, a biomedically enriched AI model, achieved the highest accuracy in generating PubMed citations for glaucoma research, outperforming general-purpose models and highlighting the necessity of human oversight to mitigate AI-related citation errors. PURPOSE: This study evaluated the accuracy and reliability of 4 artificial intelligence (AI) models-ChatGPT (OpenAI GPT-3.5), Copilot (Git...

A framework of hybrid deep learning and nature-inspired algorithms for accurate multi-class fundus disease classification.

Fundus imaging is an essential technique for detecting anatomical changes indicative of various ophthalmological diseases. These alterations-including changes in the macula, optic disc, fovea, and blood vessels-can signal conditions such as diabetic retinopathy, glaucoma, age-related macular degeneration, cataracts, and myopia. In this paper, we propose a novel hybrid framework for classifying mul...

Routine blood tests and machine learning identify complications in high myopia.

High myopia can lead to cataract, glaucoma, retinal detachment, choroidal neovascularisation, and macular degeneration, causing irreversible vision lo...

Real world practice of Artificial intelligence Diagnostic System for Diabetic Retinopathy in Taiwan.

PURPOSE: We evaluated the alterations of applying artificial intelligence (AI) diagnostic system for diabetic retinopathy (DR) screening in real-world...

Ferroptosis regulator NOX1 acts a diagnostic biomarker and mediates disease progression with the transcriptional regulation of STAT3 in glaucoma.

PURPOSE: Primary open-angle glaucoma (POAG) is the leading cause of irreversible blindness. Regrettably, the roles of ferroptosis-related (FR) genes i...

Toward Long-Term Visual Field Appearance Forecasting Using Artificial Intelligence for Ophthalmic Education and Diagnosis.

OBJECTIVE: To provide state-of-the-art, post hoc-explainable visual field (VF) forecasts to aid in training ophthalmic residents to characterize glauc...

Reply to Comment on "Artificial intelligence-guided end point selection for neuroprotection trials in glaucoma".

SYN-OCT:A synthetic dataset of ocular optical coherence tomography images from healthy and glaucoma eyes.

The SYN-OCT dataset contains a total of 200,000 synthetic cross-sectional circumpapillary optical coherence tomography (OCT) images, comprising of 100...

Reduced order modelling of air-puff test for corneal material characterisation.

Models of the fluid-structure interaction (FSI) model for the air-puff test were analysed. Using Abaqus, the air-puff test is applied to eyes with var...

HOG-CNN: Integrating Histogram of Oriented Gradients with Convolutional Neural Networks for Retinal Image Classification.

The analysis of fundus images is critical for the early detection and diagnosis of retinal diseases such as diabetic retinopathy (DR), glaucoma, and a...

Model utility and explainability in federated learning - A case study in healthcare using fundus oculi datasets.

OBJECTIVE: Introduce a case study for Federated Learning (FL) in healthcare, addressing challenges posed by patient privacy and limited large-scale da...

Deep learning-based prediction of 24-2 visual field from fundus photographs in glaucoma.

Development trajectory and trends of ultrasound biomicroscopy in glaucoma research: a comprehensive 20-year bibliometric analysis.

PURPOSE: This study conducts a comprehensive bibliometric analysis regarding the application of ultrasound biomicroscopy in glaucoma research over the...

Artificial intelligence in glaucoma diagnosis and management: Has its time come?

Adaptive Temporal Mixture of Experts for Predicting Stiffness Metrics from the Ocular Response Analyzer and Identifying Keratoconus: Stiffness Estimates from Ocular Response Analyzer.

PURPOSE: To develop a machine learning-based modeling approach for extracting elastic stiffness estimates from Ocular Response Analyzer (ORA) waveform...

Comparative Evaluation of High vs. Low-Viscosity Silicone Oil in Macula-Off Retinal Detachment: Emulsification, Inflammation and AI-assisted Biomarker Detection.

INTRODUCTION: To compare the emulsification rates, intraocular pressure (IOP) changes, and retinal hyper-reflective foci (HRF) between low-viscosity (...

Deep Learning-Based Prediction of Visual Field Mean Deviation from Numeric OCT Data in Glaucoma.

The purpose is to evaluate whether numeric optical coherence tomography (OCT) data can predict Humphrey Visual Field Analyzer (HFA) 30-2 mean deviatio...

Macula Spatial Patterns and Their Association With Central Visual Field Progression in Glaucoma Using Artificial Intelligence.

PRECIS: Artificial intelligence-derived macular thinning patterns were associated with central visual field progression in glaucoma and outperformed g...

Advancements of ultrasound modalities and their clinical potential in ophthalmology.

Ultrasound imaging has played an important role in ophthalmic diagnostics due to its real-time capability, safety, and cost-effectiveness. In recent y...

Retinal vascular alteration following surgical intraocular pressure reduction in primary angle closure disease.

AIMS: To investigate retinal vascular geometric alterations following intraocular pressure (IOP)-lowering surgery in patients with primary angle closu...