Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Glaucoma: Overview01:25

Glaucoma: Overview

1.3K
Glaucoma is an eye condition characterized by increased intraocular pressure that damages the retina and optic nerve, leading to irreversible blindness if left untreated. The human eye has various components, including the cornea, iris, pupil, lens, and optic nerve. Aqueous humor is secreted by the epithelium of the ciliary body in the posterior chamber and flows through the trabecular meshwork and canal of Schlemm, maintaining normal intraocular pressure. The trabecular meshwork and the canal...
1.3K
Open Angle Glaucoma: Treatment01:27

Open Angle Glaucoma: Treatment

963
In open-angle glaucoma, the iridocorneal angle remains open, but the trabecular meshwork becomes stiff, slowing down the outflow of aqueous humor. This causes a buildup of aqueous humor in the anterior chamber, leading to a sudden increase in intraocular pressure. The treatment for open-angle glaucoma focuses on reducing the elevated intraocular pressure by either decreasing the secretion of aqueous humor or increasing its outflow.
Drugs such as carbonic anhydrase inhibitors, α2- and...
963
Angle Closure Glaucoma: Treatment01:28

Angle Closure Glaucoma: Treatment

1.2K
Angle-closure glaucoma, or closed-angle glaucoma, is an eye condition where the iris bulges out and blocks the iridocorneal angle, resulting in a buildup of aqueous humor and increased intraocular pressure. Immediate medical attention is necessary due to the sudden onset of symptoms. The treatment for angle-closure glaucoma includes short-term and long-term approaches. Short-term treatment involves using eye drops like pilocarpine to lower intraocular pressure by increasing aqueous humor...
1.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Preseptal Cellulitis as the Presenting Sign of Systemic Inflammatory Disease Secondary to Chikungunya Virus: A Case Report.

Case reports in ophthalmology·2026
Same author

Efficacy and Safety of Preservative-Free Bimatoprost 0.01% Gel in Patients with Open-Angle Glaucoma and Ocular Hypertension: Results from Two Phase III Randomized Trials.

Clinical ophthalmology (Auckland, N.Z.)·2026
Same author

Thirty-Six-Month Multicentre Outcomes of Combined Phacoemulsification and Hydrus Microstent Implantation in Eyes With Normal Tension Glaucoma.

Journal of glaucoma·2026
Same author

A Prospective, Real-World, Multicenter Study to Support the Role of Ab-Interno Canaloplasty in Glaucoma Management.

American journal of ophthalmology·2026
Same author

Neural Network-Based Prediction of Post-Operative Visual Outcomes Following Secondary Pediatric Intraocular Lens Implantation.

Children (Basel, Switzerland)·2025
Same author

Development of a Neural Network to Predict Optimal IOP Reduction in Glaucoma Management.

Vision (Basel, Switzerland)·2025
Same journal

Subtitle Engagement Varies with Audio-Subtitle Language-Script Pairing: Evidence from Hindi-English Bilinguals with an English-Medium Instruction Background.

Vision (Basel, Switzerland)·2026
Same journal

Ultra-Early OCT Changes After Intravitreal Injection: Evidence Consistent with Transient Mechanical Compression.

Vision (Basel, Switzerland)·2026
Same journal

A Cerebral Basis for Visual Discomfort and Visual Stress.

Vision (Basel, Switzerland)·2026
Same journal

Practice Effects and the Lanthony D15.

Vision (Basel, Switzerland)·2026
Same journal

Wouldn't It Be Nice to Not Fall for It Twice? Prior Experience Does Not Abolish the Impact of Expectancy Violations on Attention Capture.

Vision (Basel, Switzerland)·2026
Same journal

Evaluation of the Efficacy of Treatment for Convergence Insufficiency with a New Digital Mobile Platform: A Comparative Preliminary Study.

Vision (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Jan 17, 2026

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential
07:11

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential

Published on: May 25, 2020

6.8K

Predicting Pattern Standard Deviation in Glaucoma: A Machine Learning Approach Leveraging Clinical Data.

Raheem Remtulla1, Patrik Abdelnour2, Daniel R Chow2

  • 1Department of Ophthalmology & Visual Sciences, McGill University, Montreal, QC H4A 0A4, Canada.

Vision (Basel, Switzerland)
|September 22, 2025
PubMed
Summary
This summary is machine-generated.

Machine learning accurately predicts pattern standard deviation (PSD) for glaucoma management using clinical data. This automated neural network (ANN) approach offers a reliable alternative to traditional visual field (VF) testing.

Keywords:
glaucomamachine learningvisual fields

More Related Videos

Laser Capture Microdissection of Highly Pure Trabecular Meshwork from Mouse Eyes for Gene Expression Analysis
13:47

Laser Capture Microdissection of Highly Pure Trabecular Meshwork from Mouse Eyes for Gene Expression Analysis

Published on: June 3, 2018

9.8K
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.1K

Related Experiment Videos

Last Updated: Jan 17, 2026

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential
07:11

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential

Published on: May 25, 2020

6.8K
Laser Capture Microdissection of Highly Pure Trabecular Meshwork from Mouse Eyes for Gene Expression Analysis
13:47

Laser Capture Microdissection of Highly Pure Trabecular Meshwork from Mouse Eyes for Gene Expression Analysis

Published on: June 3, 2018

9.8K
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.1K

Area of Science:

  • Ophthalmology
  • Artificial Intelligence
  • Medical Diagnostics

Background:

  • Visual field (VF) testing is essential for glaucoma management but faces challenges with technician availability and test reliability.
  • Developing alternative methods for VF assessment is crucial to improve patient care and diagnostic efficiency.

Purpose of the Study:

  • To investigate the potential of machine learning, specifically an automated neural network (ANN), to predict pattern standard deviation (PSD) using readily available clinical data.
  • To assess the accuracy and reliability of the ANN model in predicting PSD.

Main Methods:

  • A retrospective study utilizing publicly accessible data from 743 eyes (541 glaucoma, 202 controls).
  • An ANN model was trained using seven input features: mean retinal nerve fiber layer (RNFL), intraocular pressure (IOP), patient age, central corneal thickness (CCT), glaucoma diagnosis, study protocol, and laterality.
  • Model performance was evaluated using Root Mean Square Error (RMSE) and correlation coefficient (r), with Leave-One-Feature-Out (LOFO) analysis for feature importance.

Main Results:

  • The ANN model demonstrated strong predictive accuracy with minimal overfitting, achieving high correlation coefficients (r ≈ 0.81-0.89) and low RMSE (≈ 1.67-2.27) on training and test sets.
  • LOFO analysis identified RNFL, CCT, IOP, glaucoma status, study protocol, and age as the most significant contributors to PSD prediction.
  • The model showed construct validity, successfully predicting PSD from RNFL and clinical data.

Conclusions:

  • Neural networks can effectively predict PSD using RNFL and standard clinical inputs, offering a promising tool for glaucoma assessment.
  • This machine learning approach has the potential to predict or generate VF estimations, potentially overcoming limitations of current VF testing methods.