Glaucoma

Deep-learning-derived glaucoma-related endophenotypes enable novel genome-wide genetic and functional discovery

The genetic architecture of primary open-angle glaucoma (POAG), a leading cause of irreversible blin...

Identification of Risk Factors for Glaucoma Progression in Free-Text Clinical Notes using a Local Large Language Model

To evaluate the performance of a large language model (LLM) in identifying medication non-adherence,...

A Federated Learning-based Optic Disc and Cup Segmentation Model for Glaucoma Monitoring In Color Fundus Photographs

Glaucoma, a leading cause of blindness worldwide, depends on accurate optic nerve head assessment, p...

Glaucoma Detection Using Deep Learning and Prompt-Based Explainable Report Generation

Glaucoma is a leading cause of irreversible blindness and requires early detection to prevent vision...

Leveraging molecular-QTL co-association to predict novel disease-associated genetic loci using a graph convolutional neural network.

Genome-wide association studies (GWAS) have successfully uncovered numerous associations between gen...

[Primary angle closure suspects: application of machine learning method for substantiation of close monitoring].

UNLABELLED: One of the priority areas in healthcare is the concept of predictive, preventive and per...

DiffuPT: Class Imbalance Mitigation for Glaucoma Detection via Diffusion Based Generation and Model Pretraining

Glaucoma is a progressive optic neuropathy characterized by structural damage to the optic nerve h...

Identification and validation of oxidative stress-related genes in primary open-angle glaucoma by weighted gene co-expression network analysis and machine learning.

Primary open-angle glaucoma (POAG) is a common ocular disease, and there is currently no effective t...

A Computational Fluid Dynamics study of drug-releasing ocular implants for glaucoma treatment: Comparison of implant size and locations

Drug-releasing implants are gaining momentum in the treatment of glaucoma. Implants present howeve...

Beyond PhacoTrainer: Deep Learning for Enhanced Trabecular Meshwork Detection in MIGS Videos.

PURPOSE: The purpose of this study was to develop deep learning models for surgical video analysis, ...

Long-Term Rate of Optic Disc Rim Loss in Glaucoma Patients Measured From Optic Disc Photographs With a Deep Neural Network.

PURPOSE: This study uses deep neural network-generated rim-to-disc area ratio (RADAR) measurements a...

Using Multi-Layer Perceptron Driven Diagnosis to Compare Biomarkers for Primary Open Angle Glaucoma.

PURPOSE: To use neural network machine learning (ML) models to identify the most relevant ocular bio...

Hybrid convolutional neural network optimized with an artificial algae algorithm for glaucoma screening using fundus images.

OBJECTIVE: We developed an optimized decision support system for retinal fundus image-based glaucoma...

How Interoperability Can Enable Artificial Intelligence in Clinical Applications.

This paper explores the critical role of Interoperability (IOP) in the integration of Artificial Int...

Deep Learning to Predict Glaucoma Progression using Structural Changes in the Eye

Glaucoma is a chronic eye disease characterized by optic neuropathy, leading to irreversible visio...

A Hybrid Deep Learning Classification of Perimetric Glaucoma Using Peripapillary Nerve Fiber Layer Reflectance and Other OCT Parameters from Three Anatomy Regions

Precis: A hybrid deep-learning model combines NFL reflectance and other OCT parameters to improve ...

Visual Field Prognosis From Macula and Circumpapillary Spectral Domain Optical Coherence Tomography.

PURPOSE: To explore the structural-functional loss relationship from optic-nerve-head- and macula-ce...

Predicting Glaucoma Surgical Outcomes Using Neural Networks and Machine Learning on Electronic Health Records.

PURPOSE: To develop machine learning (ML) and deep learning (DL) models to predict glaucoma surgical...

Comment on: Artificial intelligence chatbot and Academy Preferred Practice Pattern ® Guidelines on cataract and glaucoma.

Reply: Artificial intelligence chatbot and Academy Preferred Practice Pattern® Guidelines on cataract and glaucoma.

Quantitative Assessment of Fundus Tessellated Density in Highly Myopic Glaucoma Using Deep Learning.

PURPOSE: To characterize the fundus tessellated density (FTD) in highly myopic glaucoma (HMG) and hi...