Glaucoma

A novel lightweight deep learning approach for simultaneous optic cup and optic disc segmentation in glaucoma detection.

Glaucoma is a chronic neurodegenerative disease that can result in irreversible vision loss if not t...

Prediction of multiclass surgical outcomes in glaucoma using multimodal deep learning based on free-text operative notes and structured EHR data.

OBJECTIVE: Surgical outcome prediction is challenging but necessary for postoperative management. Cu...

Deep Learning Identifies High-Quality Fundus Photographs and Increases Accuracy in Automated Primary Open Angle Glaucoma Detection.

PURPOSE: To develop and evaluate a deep learning (DL) model to assess fundus photograph quality, and...

A neural network model for predicting the effectiveness of treatment in patients with neovascular glaucoma associated with diabetes mellitus.

INTRODUCTION: The study hypothesizes that neural networks can be an effective tool for predicting tr...

Identifying Hub Genes for Glaucoma based on Bulk RNA Sequencing Data and Multi-machine Learning Models.

AIMS: The aims of this study were to determine hub genes in glaucoma through multiple machine learni...

Deep Learning-based Glaucoma Detection Using CNN and Digital Fundus Images: A Promising Approach for Precise Diagnosis.

BACKGROUND: Glaucoma is a significant cause of irreversible blindness worldwide, with symptoms often...

[Application of artificial intelligence in glaucoma. Part 1. Neural networks and deep learning in glaucoma screening and diagnosis].

This article reviews literature on the use of artificial intelligence (AI) for screening, diagnosis,...

Multi-dimensional dense attention network for pixel-wise segmentation of optic disc in colour fundus images.

BACKGROUND: Segmentation of retinal fragments like blood vessels, Optic Disc (OD), and Optic Cup (OC...

[Application of artificial intelligence in glaucoma. Part 2. Neural networks and machine learning in the monitoring and treatment of glaucoma].

The second part of the literature review on the application of artificial intelligence (AI) methods ...

Validating the Generalizability of Ophthalmic Artificial Intelligence Models on Real-World Clinical Data.

PURPOSE: This study aims to investigate generalizability of deep learning (DL) models trained on com...

Artifact Correction in Retinal Nerve Fiber Layer Thickness Maps Using Deep Learning and Its Clinical Utility in Glaucoma.

PURPOSE: Correcting retinal nerve fiber layer thickness (RNFLT) artifacts in glaucoma with deep lear...

Improving the Accuracy and Speed of Visual Field Testing in Glaucoma With Structural Information and Deep Learning.

PURPOSE: To assess the performance of a perimetric strategy using structure-function predictions fro...

A New Wavelet Collocation Algorithm for Solving a Nonlinear Boundary Value Problem of the Human Corneal Shape.

The Hermite wavelet method (HWM) is introduced in this study to solve a nonlinear differential equat...

Efficacy of deep learning-based artificial intelligence models in screening and referring patients with diabetic retinopathy and glaucoma.

PURPOSE: To analyze the efficacy of a deep learning (DL)-based artificial intelligence (AI)-based al...

3-LbNets: Tri-Labeling Deep Convolutional Neural Network for the Automated Screening of Glaucoma, Glaucoma Suspect, and No Glaucoma in Fundus Images.

Early detection of glaucoma, a widespread visual disease, can prevent vision loss. Unfortunately, op...

Population stratification strategies in artificial intelligence-based glaucoma monitoring, "corneal anthropology" to bridge gap between genetics and clinics?

Medical Application of Geometric Deep Learning for the Diagnosis of Glaucoma.

PURPOSE: (1) To assess the performance of geometric deep learning in diagnosing glaucoma from a sing...

Importance and use of corneal biomechanics and its diagnostic utility.

The study of corneal biomechanics has become relevant in recent years due to its possible applicatio...

Evaluation of Generative Adversarial Networks for High-Resolution Synthetic Image Generation of Circumpapillary Optical Coherence Tomography Images for Glaucoma.

IMPORTANCE: Deep learning (DL) networks require large data sets for training, which can be challengi...

Pointwise Visual Field Estimation From Optical Coherence Tomography in Glaucoma Using Deep Learning.

PURPOSE: Standard automated perimetry is the gold standard to monitor visual field (VF) loss in glau...

Investigation of the Role of Convolutional Neural Network Architectures in the Diagnosis of Glaucoma using Color Fundus Photography.

OBJECTIVES: To evaluate the performance of convolutional neural network (CNN) architectures to disti...