Glaucoma

Artificial intelligence in glaucoma detection using color fundus photographs.

PURPOSE: To explore the potential of artificial intelligence (AI) for glaucoma detection using deep learning algorithm and evaluate its accuracy for image classification of glaucomatous optic neuropathy (GON) from color fundus photographs.

Evaluation of Verteporfin as a Novel Antifibrotic Agent in a Rabbit Model of Glaucoma Filtration Surgery: A Pilot Study.

PURPOSE: Verteporfin is a benzoporphyrin derivative which is Food and Drug Administration-approved for treatment of choroidal neovascularization in conjunction with photodynamic therapy. It has been shown to prevent fibrosis and scar formation in several organs and represents a promising novel antifibrotic agent for glaucoma surgery. The goal of this study is to determine the effect of verteporfin...

Efficient feature selection based novel clinical decision support system for glaucoma prediction from retinal fundus images.

The process of feature selection (FS) is vital aspect of machine learning (ML) model's performance enhancement where the objective is the selection of...

Prediction Models for Glaucoma in a Multicenter Electronic Health Records Consortium: The Sight Outcomes Research Collaborative.

PURPOSE: Advances in artificial intelligence have enabled the development of predictive models for glaucoma. However, most work is single-center and u...

Artificial intelligence for glaucoma: state of the art and future perspectives.

PURPOSE OF REVIEW: To address the current role of artificial intelligence (AI) in the field of glaucoma.

Exploring large language model for next generation of artificial intelligence in ophthalmology.

In recent years, ophthalmology has advanced significantly, thanks to rapid progress in artificial intelligence (AI) technologies. Large language model...

ChatGPT: is it good for our glaucoma patients?

PURPOSE: Our study investigates ChatGPT and its ability to communicate with glaucoma patients.

Predicting glaucoma progression using deep learning framework guided by generative algorithm.

Glaucoma is a slowly progressing optic neuropathy that may eventually lead to blindness. To help patients receive customized treatment, predicting how...

Editorial: Translational opportunities for AI in glaucoma.

Assessment of angle closure disease in the age of artificial intelligence: A review.

Primary angle closure glaucoma is a visually debilitating disease that is under-detected worldwide. Many of the challenges in managing primary angle c...

Computational methods in glaucoma research: Current status and future outlook.

Advancements in computational techniques have transformed glaucoma research, providing a deeper understanding of genetics, disease mechanisms, and pot...

Deep learning visual field global index prediction with optical coherence tomography parameters in glaucoma patients.

The aim of this study was to predict three visual filed (VF) global indexes, mean deviation (MD), pattern standard deviation (PSD), and visual field i...

Deep Learning Application to Detect Glaucoma with a Mixed Training Approach: Public Database and Expert-Labeled Glaucoma Population.

INTRODUCTION: Artificial intelligence has real potential for early identification of ocular diseases such as glaucoma. An important challenge is the r...

Autonomous assessment of spontaneous retinal venous pulsations in fundus videos using a deep learning framework.

The presence or absence of spontaneous retinal venous pulsations (SVP) provides clinically significant insight into the hemodynamic status of the opti...

The Relationship Between Artificial Intelligence-Assisted OCT Angiography-Derived Foveal Avascular Zone Parameters and Visual-Field Defect Progression in Eyes with Open-Angle Glaucoma.

PURPOSE: To investigate clinical factors associated with foveal avascular zone (FAZ) parameters obtained using OCT angiography (OCTA) with assistance ...

Smartphone Eye Examination: Artificial Intelligence and Telemedicine.

The current medical scenario is closely linked to recent progress in telecommunications, photodocumentation, and artificial intelligence (AI). Smartp...

A deep learning approach to investigate the filtration bleb functionality after glaucoma surgery: a preliminary study.

PURPOSE: To distinguish functioning from failed filtration blebs (FBs) implementing a deep learning (DL) model on slit-lamp images.

Early Detection of Optic Nerve Changes on Optical Coherence Tomography Using Deep Learning for Risk-Stratification of Papilledema and Glaucoma.

BACKGROUND: The use of artificial intelligence is becoming more prevalence in medicine with numerous successful examples in ophthalmology. However, mu...

Deep Learning for Inference of Hepatic Proton Density Fat Fraction From T1-Weighted In-Phase and Opposed-Phase MRI: Retrospective Analysis of Population-Based Trial Data.

The confounder-corrected chemical shift-encoded MRI (CSE-MRI) sequence used to determine proton density fat fraction (PDFF) for hepatic fat quantific...

Multimodal Deep Learning Classifier for Primary Open Angle Glaucoma Diagnosis Using Wide-Field Optic Nerve Head Cube Scans in Eyes With and Without High Myopia.

PRCIS: An optical coherence tomography (OCT)-based multimodal deep learning (DL) classification model, including texture information, is introduced th...