Glaucoma

Comparison of response surface methodology and artificial neural network to optimize novel ophthalmic flexible nano-liposomes: Characterization, evaluation, in vivo pharmacokinetics and molecular dynamics simulation.

To improve the topical delivery of pilocarpine hydrochloride (PN) to treat glaucoma, flexible nano-liposomes containing PN (PN-FLs) were prepared, optimized and characterized. Artificial neural network (ANN) and response surface methodology (RSM) were used to optimize the procedure and to obtain an optimal formulation. The properties of PN-FLs were investigated, including particle size, zeta poten...

Use of Machine Learning on Contact Lens Sensor-Derived Parameters for the Diagnosis of Primary Open-angle Glaucoma.

PURPOSE: To test the hypothesis that contact lens sensor (CLS)-based 24-hour profiles of ocular volume changes contain information complementary to intraocular pressure (IOP) to discriminate between primary open-angle glaucoma (POAG) and healthy (H) eyes.

Comparison of Machine-Learning Classification Models for Glaucoma Management.

This study develops an objective machine-learning classification model for classifying glaucomatous optic discs and reveals the classificatory criteri...

Detection of Longitudinal Visual Field Progression in Glaucoma Using Machine Learning.

PURPOSE: Global indices of standard automated perimerty are insensitive to localized losses, while point-wise indices are sensitive but highly variabl...

Deep learning in ophthalmology: a review.

Deep learning is an emerging technology with numerous potential applications in Ophthalmology. Deep learning tools have been applied to different diag...

Structure-Preserving Guided Retinal Image Filtering and Its Application for Optic Disk Analysis.

Retinal fundus photographs have been used in the diagnosis of many ocular diseases such as glaucoma, pathological myopia, age-related macular degenera...

Classification of optic disc shape in glaucoma using machine learning based on quantified ocular parameters.

PURPOSE: This study aimed to develop a machine learning-based algorithm for objective classification of the optic disc in patients with open-angle gla...

A Novel Adaptive Deformable Model for Automated Optic Disc and Cup Segmentation to Aid Glaucoma Diagnosis.

This paper proposes a novel Adaptive Region-based Edge Smoothing Model (ARESM) for automatic boundary detection of optic disc and cup to aid automatic...

The application of artificial neural networks and support vector regression for simultaneous spectrophotometric determination of commercial eye drop contents.

In the present study, artificial neural networks (ANNs) and support vector regression (SVR) as intelligent methods coupled with UV spectroscopy for si...

Predictions of ocular changes caused by diabetes in glaucoma patients.

BACKGROUND AND OBJECTIVE: This paper builds different neural network models with simple topologies, having one or two hidden layers which were subsequ...

Underwater Inherent Optical Properties Estimation Using a Depth Aided Deep Neural Network.

Underwater inherent optical properties (IOPs) are the fundamental clues to many research fields such as marine optics, marine biology, and underwater ...

Artificial neural networks as alternative tool for minimizing error predictions in manufacturing ultradeformable nanoliposome formulations.

This work was aimed at determining the feasibility of artificial neural networks (ANN) by implementing backpropagation algorithms with default setting...

Development of machine learning models for diagnosis of glaucoma.

The study aimed to develop machine learning models that have strong prediction power and interpretability for diagnosis of glaucoma based on retinal n...

A machine-learning graph-based approach for 3D segmentation of Bruch's membrane opening from glaucomatous SD-OCT volumes.

Bruch's membrane opening-minimum rim width (BMO-MRW) is a recently proposed structural parameter which estimates the remaining nerve fiber bundles in ...

Evaluation of topical bevacizumab as an adjunct to mitomycin C augmented trabeculectomy.

PURPOSE: To investigate the safety and synergistic effect of topical bevacizumab after trabeculectomy surgery with mitomycin C (MMC).

Glaucoma detection using entropy sampling and ensemble learning for automatic optic cup and disc segmentation.

We present a novel method to segment retinal images using ensemble learning based convolutional neural network (CNN) architectures. An entropy samplin...

Machine Learning Techniques in Clinical Vision Sciences.

This review presents and discusses the contribution of machine learning techniques for diagnosis and disease monitoring in the context of clinical vis...

Pigment Dispersion Syndrome Progression to Pigmentary Glaucoma in a Latin American Population.

OBJECTIVE: To determine the progression of pigment dispersion syndrome (PDS) into pigmentary glaucoma (PG) in a population at the Central Military Hos...

Learning ECOC Code Matrix for Multiclass Classification with Application to Glaucoma Diagnosis.

Classification of different mechanisms of angle closure glaucoma (ACG) is important for medical diagnosis. Error-correcting output code (ECOC) is an e...

A Hybrid Swarm Algorithm for optimizing glaucoma diagnosis.

Glaucoma is among the most common causes of permanent blindness in human. Because the initial symptoms are not evident, mass screening would assist ea...