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

629
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...
629
Angle Closure Glaucoma: Treatment01:28

Angle Closure Glaucoma: Treatment

575
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...
575
Open Angle Glaucoma: Treatment01:27

Open Angle Glaucoma: Treatment

481
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...
481

You might also read

Related Articles

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

Sort by
Same author

Benchmarking GPT-5, LLaMA, and Mistral for Clinical Named Entity Recognition in Ophthalmology Progress Notes.

Translational vision science & technology·2026
Same author

Pharmaceutical Manufacturing in China Innovation Performance: A Dynamic QCA Analysis Based on the WSR Perspective.

ClinicoEconomics and outcomes research : CEOR·2026
Same author

Improving Fairness and Mitigating Bias in Multicenter Electronic Health Records Models to Predict Glaucoma Outcomes.

Ophthalmology science·2026
Same author

Decline of Visual Function and Risk of Legal Blindness With Age in RPGR -Associated Retinal Degeneration: A Multicenter Study.

Clinical & experimental ophthalmology·2026
Same author

Addressing Generalizability in Clinical Named Entity Recognition: Federated Learning or Large Language Models?: A Case Study on Visual Acuity Extraction from US and UK Eye Institutes.

AMIA ... Annual Symposium proceedings. AMIA Symposium·2026
Same author

How Far Have Large Language Models Advanced in Ophthalmology? A Systematic Review of Their Development, Evaluation, and Readiness for Clinical Use.

Research square·2026

Related Experiment Video

Updated: Jul 24, 2025

Full-Circle Cauterization of Limbal Vascular Plexus for Surgically Induced Glaucoma in Rodents
10:10

Full-Circle Cauterization of Limbal Vascular Plexus for Surgically Induced Glaucoma in Rodents

Published on: February 15, 2022

1.5K

Predicting Glaucoma Progression to Surgery with Artificial Intelligence Survival Models.

Shiqi Tao1, Rohith Ravindranath1, Sophia Y Wang1

  • 1Byers Eye Institute, Department of Ophthalmology, Stanford University, Palo Alto, California.

Ophthalmology Science
|July 7, 2023
PubMed
Summary

New artificial intelligence (AI) survival models accurately predict glaucoma progression to surgery. Deep learning and tree-based models outperformed traditional methods, offering improved clinical decision support for ophthalmic outcomes.

Keywords:
Artificial intelligenceDeep learningElectronic health recordsGlaucomaMachine Learning

More Related Videos

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.3K
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

9.4K

Related Experiment Videos

Last Updated: Jul 24, 2025

Full-Circle Cauterization of Limbal Vascular Plexus for Surgically Induced Glaucoma in Rodents
10:10

Full-Circle Cauterization of Limbal Vascular Plexus for Surgically Induced Glaucoma in Rodents

Published on: February 15, 2022

1.5K
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.3K
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

9.4K

Area of Science:

  • Ophthalmology
  • Artificial Intelligence
  • Medical Informatics

Background:

  • Traditional artificial intelligence (AI) models for predicting glaucoma progression do not account for the longitudinal nature of patient follow-up.
  • Developing accurate predictive models is crucial for timely surgical intervention in glaucoma management.

Purpose of the Study:

  • To develop and compare survival-based AI models for predicting glaucoma patients' progression to surgery.
  • To evaluate the performance of regression, tree-based, and deep learning approaches in predicting glaucoma surgery.

Main Methods:

  • A retrospective observational study utilizing electronic health records (EHRs) from 4512 glaucoma patients.
  • Trained AI survival models including penalized Cox proportional hazards (CPH) with PCA, random survival forests (RSFs), gradient-boosting survival (GBS), and DeepSurv.
  • Model performance evaluated using concordance index (C-index) and mean cumulative/dynamic area under the curve (mean AUC).

Main Results:

  • The DeepSurv model demonstrated the best performance (C-index: 0.775, mean AUC: 0.802).
  • Tree-based models (RSF and GBS) also showed strong performance, outperforming the CPH model.
  • Predicted cumulative hazard curves effectively distinguished between patients undergoing early surgery, late surgery, or no surgery.

Conclusions:

  • AI survival models utilizing EHR data can effectively predict glaucoma progression to surgery.
  • Tree-based and deep learning models are superior to traditional regression models for high-dimensional glaucoma data.
  • Future research should focus on advanced deep learning survival models incorporating diverse data types.