Glaucoma

Predicting worsening visual field via masked dual stage attention recurrent neural network.

Based on dual-stage attention recurrent neural network (DA-RNN), a masked DA-RNN (MDA-RNN) model was developed to predict future visual fields (VF). The training dataset comprised 154,105 VF examinations of 22,404 eyes. Performance was measured as the mean absolute error (MAE) between the predicted and actual values of mean deviation (MD), pattern standard deviation (PSD), Visual Field Index (VFI)...

Therapeutic ultrasound in ophthalmology: a comprehensive review.

BACKGROUND: Therapeutic ultrasound has emerged as a promising noninvasive or minimally invasive modality in ophthalmology, offering novel solutions across a range of ocular disorders. This review summarizes the current advances in both the underlying biophysical mechanisms and their translation into clinical and experimental applications. METHODS: This review synthesizes and analyzes the current l...

A hybrid dual-stream CNN framework with dynamic data augmentation and improved Manta Ray Foraging Optimization for robust glaucoma detection.

A progressive neurological condition, glaucoma is one of the main causes of irreversible blindness in the globe. Early detection is crucial to prevent...

Deep learning in population-based screening for glaucoma.

BACKGROUND/AIMS: Deep learning algorithms have shown promise for glaucoma detection using retinal imaging. The Northern Finland Birth Cohort Eye Study...

A hybrid framework for effective microscopic cell counting segmentation integrating Light-U-net with watershed.

Glaucoma is a major cause of irreversible blindness worldwide, resulting in the progressive degeneration of retinal ganglion cellss (RGCs), which make...

Predicting 10-2 SITA Standard from 24-2C SITA Faster: Development and Validation of Deep24-2C.

PURPOSE: To develop and validate Deep24-2C, a machine learning (ML) model that reconstructs comprehensive Humphrey Field Analyzer (HFA) 10-2 visual fi...

MaxGRNet: A multi-axis vision transformer with improved generalization for eye disease classification using explainable AI with insertion-deletion operations on fundus images.

Eye diseases, including diabetic retinopathy (DR), glaucoma, and cataracts, represent a major global health concern and can lead to severe visual impa...

Integrating generative AI and genetic causal inference identifies metformin as a repurposing candidate for normal tension glaucoma.

The normal tension glaucoma (NTG) has limited drug options since current antiglaucoma medications are mostly designed to decrease intraocular pressure...

Prediction of primary glaucoma: development and validation of multiple machine learning models.

Glaucomatous Remodeling of the Lamina Cribrosa: Association With Visual Field Progression.

PURPOSE: To determine whether rates of change in lamina cribrosa (LC) depth and curvature in POAG patients are associated with rates of visual field (...

A novel superpixel based Vision Transformer for improving interpretability in glaucoma screening.

Interpretability remains one of the major challenges in the clinical adoption of deep learning models for medical image analysis. In ophthalmology, pa...

Improving support and self-management of ophthalmic patients using an artificial intelligence health coach.

This study evaluates patient engagement and satisfaction with Everyday Medical Monitoring Ally (E.M.M.A), a purpose-trained artificial intelligence (A...

A vision transformer model for the detection of glaucoma from optic disc photographs.

This study uses a deep learning algorithm to analyze optic disc photographs (ODPs) and classify eyes as glaucomatous or healthy based on optic nerve a...

A Knowledge-Guided Bi-Modal Network for the Classification of Anterior Chamber Angle Images.

Glaucoma is a leading cause of irreversible blindness globally. When glaucoma is diagnosed, Anterior Chamber Angle (ACA) evaluation is the necessary s...

Predicting Visual Field Loss in Glaucoma Using OCT and Deep Learning: A Comparative Study of U-Net Variants.

PURPOSE: Glaucoma is a chronic eye disease that progressively damages the optic nerve, leading to irreversible visual field (VF) loss. OCT and VF test...

Attention‑Guided Hybrid Deep Learning with Fibonacci and Annular Ring Handcrafted Features for Glaucoma Detection in Retinal Images.

Glaucoma, a major contributor to irreversible blindness, often progresses silently, making early detection vital. Manual interpretation of retinal fun...

Comprehensive Evaluation of ChatGPT's Diagnostic Accuracy on Image-based Ophthalmic Case Interpretations.

OBJECTIVE: To evaluate the diagnostic and treatment accuracy of Chat Generative Pre-trained Transformer (GPT-4.o) in ophthalmology, comparing performa...

Interpretable machine learning reveals metabolomic signatures: biomarkers and mechanisms in acute vs chronic angle-closure glaucoma.

CorvisST biomechanical indices in the diagnosis of corneal stromal and endothelial disorders: an artificial intelligence-based comparative study.

AIMS: To analyse the value of the CorvisST indices in diagnosing corneal stromal and endothelial disorders (CSEDs). METHODS: This institutional retros...

Fuzzy logic for preanesthetic risk assessment in cataract surgery patients.

We aimed to build a fuzzy logic preanaesthetic risk score tailored to cataract surgery. By fusing systemic comorbidities with key patient attributes i...