Glaucoma

Synergistic AI-resident approach achieves superior diagnostic accuracy in tertiary ophthalmic care for glaucoma and retinal disease.

INTRODUCTION: Artificial intelligence (AI) shows promise in ophthalmology, but its potential in tertiary care settings in Latin America remains understudied. We present a Mexican AI-powered screening tool and evaluate it against first-year ophthalmology residents in a tertiary care setting in Mexico City.

State of the Art on Inherited Retinal Dystrophies: Management and Molecular Genetics.

Inherited retinal dystrophies (IRDs) represent a group of heterogeneous disorders caused by gene mutations primarily affecting retinal photoreceptors. In addition to vision loss, other symptoms may lead to visual impairment, such as altered visual fields, hemeralopia, glare sensitivity, and impaired color vision. These conditions almost always complicate with the onset of cataracts, macular edema ...

Restoring AIBP expression in the retina provides neuroprotection in glaucoma.

Glaucoma is a neurodegenerative disease manifested by retinal ganglion cell (RGC) death and irreversible blindness. We have identified apolipoprotein ...

Keypoint localization and parameter measurement in ultrasound biomicroscopy anterior segment images based on deep learning.

BACKGROUND: Accurate measurement of anterior segment parameters is crucial for diagnosing and managing ophthalmic conditions, such as glaucoma, catara...

Prediction of perimetric progression in ocular hypertension and open angle glaucoma based on corneal biomechanics.

PurposeTo identify parameters that are significant risk predictors of visual field (VF) progression in patients with ocular hypertension (OHT) or earl...

Deep learning-assisted 10-μL single droplet-based viscometry for human aqueous humor.

Probing the viscosity of human aqueous humor is crucial for optimizing micro-tube shunts in glaucoma treatment. However, conventional viscometers are ...

Enhanced glaucoma classification through advanced segmentation by integrating cup-to-disc ratio and neuro-retinal rim features.

Glaucoma is a progressive eye condition caused by high intraocular fluid pressure, damaging the optic nerve, leading to gradual, irreversible vision l...

Risk for ocular hypertension progression to early glaucoma: A predictive model and key predictors.

BACKGROUND: Ocular hypertension (OHT) is the most significant risk factor for glaucoma. We aimed to develop a model for predicting OHT progression to ...

Optimized glaucoma detection using HCCNN with PSO-driven hyperparameter tuning.

. This study is focused on creating an effective glaucoma detection system employing a Hybrid Centric Convolutional Neural Network (HCCNN) model. By u...

SMOTE-Enhanced Explainable Artificial Intelligence Model for Predicting Visual Field Progression in Myopic Normal Tension Glaucoma.

PRCIS: The AI model, enhanced by SMOTE to balance data classes, accurately predicted visual field deterioration in patients with myopic normal tension...

Two-stage color fundus image registration via Keypoint Refinement and Confidence-Guided Estimation.

Color fundus images are widely used for diagnosing diseases such as Glaucoma, Cataracts, and Diabetic Retinopathy. The registration of color fundus im...

Automated learning of glaucomatous visual fields from OCT images using a comprehensive, segmentation-free 3D convolutional neural network model.

A segmentation-free 3D Convolutional Neural Network (3DCNN) model was adopted to estimate Visual Field (VF) in glaucoma cases using Optical Coherence ...

Influence of artificial intelligence on ophthalmologists' judgments in glaucoma.

PURPOSE: To examine the influence of artificial intelligence (AI) on physicians' judgments regarding the presence and severity of glaucoma on fundus p...

Grey wolf optimization technique with U-shaped and capsule networks-A novel framework for glaucoma diagnosis.

The worldwide prevalence of glaucoma makes it a major reason for blindness thus proper early diagnosis remains essential for preventing major vision d...

Optimizing deep learning models for glaucoma screening with vision transformers for resource efficiency and the pie augmentation method.

Glaucoma is the leading cause of irreversible vision impairment, emphasizing the critical need for early detection. Typically, AI-based glaucoma scree...

PyGlaucoMetrics: A Stacked Weight-Based Machine Learning Approach for Glaucoma Detection Using Visual Field Data.

: Glaucoma (GL) classification is crucial for early diagnosis and treatment, yet relying solely on stand-alone models or International Classification ...

Application of machine learning techniques in GlaucomAI system for glaucoma diagnosis and collaborative research support.

This paper proposes an architecture of the system that provides support for collaborative research focused on analysis of data acquired using Triggerf...

Deep Learning-Driven Glaucoma Medication Bottle Recognition: A Multilingual Clinical Validation Study in Patients with Impaired Vision.

OBJECTIVE: To clinically validate a convolutional neural network (CNN)-based Android smartphone app in the identification of topical glaucoma medicati...

Enhancing Ophthalmic Diagnosis and Treatment with Artificial Intelligence.

The integration of artificial intelligence (AI) in ophthalmology is transforming the field, offering new opportunities to enhance diagnostic accuracy,...

Comparison of Deep Learning and Clinician Performance for Detecting Referable Glaucoma from Fundus Photographs in a Safety Net Population.

PURPOSE: Develop and test a deep learning (DL) algorithm for detecting referable glaucoma.