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Related Concept Videos

Glaucoma: Overview01:25

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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...
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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.
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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...
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Applications of Large Language Models in Glaucoma: A Scoping Review.

Giovanni Rubegni1, Alessandra Cartocci2, Alessio Luschi2

  • 1Ophthalmology Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, 53100 Siena, Italy.

Vision (Basel, Switzerland)
|February 20, 2026
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Summary

Large language models (LLMs) and vision-language models (VLMs) show promise in glaucoma care for patient education and decision support. However, they currently function best as assistive tools due to accuracy and integration limitations.

Keywords:
ChatGPTartificial intelligenceclinical decision supportglaucomalarge language modelspatient educationvision-language models

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Area of Science:

  • Ophthalmology
  • Artificial Intelligence
  • Medical Informatics

Background:

  • Large language models (LLMs) and vision-language models (VLMs) are increasingly used in ophthalmology for patient education, diagnosis, and surgical support.
  • Their capabilities in processing medical information make them valuable for glaucoma care.

Purpose of the Study:

  • To conduct a scoping review of LLMs and VLMs in glaucoma.
  • To summarize their applications, performance, and limitations to inform future research and clinical use.

Main Methods:

  • Systematic literature search across major databases (PubMed, Scopus, Web of Science, arXiv, IEEE Xplore) from 2014 to July 2025.
  • Inclusion of studies on LLMs/VLMs in glaucoma for diagnosis, education, or surgical support.
  • Screening and review by two independent reviewers following PRISMA-ScR guidelines.

Main Results:

  • 27 studies met inclusion criteria from 316 identified records.
  • Applications were categorized into patient education (11 studies), diagnosis/risk prediction (10 studies), and surgical management (6 studies).

Conclusions:

  • LLMs are currently best suited as assistive tools in glaucoma care, not autonomous systems.
  • Potential is high for patient communication and text-based decision support, but accuracy and multimodal integration need improvement.
  • Future work should focus on domain-specific LLMs, enhanced multimodal fusion, patient readability, and ethical frameworks.