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

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...
Open Angle Glaucoma: Treatment01:27

Open Angle Glaucoma: Treatment

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...
Angle Closure Glaucoma: Treatment01:28

Angle Closure Glaucoma: Treatment

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...

You might also read

Related Articles

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

Sort by
Same author

Outcomes of Ab Interno 63 µm vs. 45 µm XEN<sup>®</sup> Gel Stent in Open-Angle Glaucoma: A Five-Year Follow-Up Study.

Journal of clinical medicine·2026
Same author

Optimizing topical glaucoma treatment outcomes: When less is better. A review on the clinical benefits of reducing treatment burden in glaucoma management.

European journal of ophthalmology·2026
Same author

Complications of silicone oil in vitreoretinal surgery: a narrative review of clinical and experimental evidence.

International journal of retina and vitreous·2026
Same author

Referral for glaucoma surgery and types of surgery in different European regions in 2025, the EURACCUR study.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie·2026
Same author

Metabolomic Analysis of Aqueous Humor to Predict Glaucoma Progression and Overall Survival After Glaucoma Surgery-The MISO II Study.

Metabolites·2026
Same author

Deep Eutectic Solvents as Green Media for Catalyst Synthesis in Advanced Oxidation Processes.

Molecules (Basel, Switzerland)·2026

Related Experiment Video

Updated: Jun 28, 2026

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss
07:12

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss

Published on: April 11, 2025

Deep learning in glaucoma referral: Performance assessment using a real-world setting.

Afonso Lima-Cabrita1,2,3, Rafael Correia Barão1,3, Diogo Bernardo Matos1,3

  • 1Ophthalmology Department, Unidade Local de Saúde Lisboa Santa Maria, Lisbon, Portugal.

Acta Ophthalmologica
|June 27, 2026
PubMed
Summary
This summary is machine-generated.

A deep learning model accurately identified all glaucoma cases among referred patients, potentially reducing unnecessary referrals by over a third. This AI tool shows promise as a pre-referral filter in glaucoma screening.

Keywords:
artificial intelligencedeep learningglaucomaglaucoma referralophthalmology

Related Experiment Videos

Last Updated: Jun 28, 2026

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss
07:12

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss

Published on: April 11, 2025

Area of Science:

  • Ophthalmology
  • Artificial Intelligence in Healthcare
  • Medical Imaging Analysis

Background:

  • Glaucoma diagnosis relies on specialist evaluation, leading to high referral rates.
  • Current referral pathways can be inefficient, with a low prevalence of glaucoma in referred patients.
  • Developing automated screening tools is crucial for optimizing healthcare resource allocation.

Purpose of the Study:

  • To assess the efficacy of a deep learning (DL) model as a pre-referral filter for detecting referable glaucoma.
  • To evaluate the model's performance using colour fundus photographs (CFPs) compared to expert clinical judgment.

Main Methods:

  • A retrospective cohort study included 96 patients referred for glaucoma evaluation.
  • A DL model analyzed CFPs, with a simulated referral triggered if the output exceeded a threshold of 0.73.
  • Model predictions were compared against glaucoma diagnoses made by expert clinicians.

Main Results:

  • The DL model achieved 100% sensitivity in identifying glaucoma cases.
  • A model-led referral system could have reduced overall referrals by 37.5% without missing any glaucoma diagnoses.
  • The model demonstrated a specificity of 0.65 and a positive predictive value of 0.41.

Conclusions:

  • The deep learning model accurately identified all glaucoma patients, demonstrating its potential to streamline referrals.
  • Implementing this AI-driven system could significantly reduce unnecessary specialist consultations.
  • The model's performance supports its use as an effective filter in the pre-referral stage for glaucoma care.