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Related Concept Videos

Glaucoma: Overview01:25

Glaucoma: Overview

1.2K
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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Open Angle Glaucoma: Treatment01:27

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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.
Drugs such as carbonic anhydrase inhibitors, α2- and...
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Angle Closure Glaucoma: Treatment01:28

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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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Related Experiment Video

Updated: Jan 7, 2026

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An Artificial Intelligence-Based Prognostic Model for Prediction of Functional Glaucoma Progression From Clinical and

Vahid Mohammadzadeh1, Sean Wu2, Sajad Besharati3

  • 1From the Glaucoma Division (V.M., S.B., M.R., Y.B., A.M., J.Z., E.K., K.E., E.M., J.C., K.N.M.), Stein Eye Institute, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA; Department of Ophthalmology and Vision Sciences (V.M.), University of Louisville, Louisville, Kentucky, USA.

American Journal of Ophthalmology
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Summary

A new deep learning model accurately predicts glaucoma progression using clinical and imaging data, outperforming human experts. This advancement offers crucial insights for diagnosing and managing glaucoma.

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Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Glaucoma diagnosis and progression prediction require integrating diverse data sources.
  • Current methods for forecasting glaucoma progression have limitations.

Purpose of the Study:

  • To develop and evaluate a deep learning (DL) model for predicting functional glaucoma progression.
  • To compare the DL model's prognostic accuracy against that of clinical experts.

Main Methods:

  • A retrospective cohort of 1,599 eyes with glaucoma was analyzed.
  • A convolutional neural network was trained on clinical data, disc photographs, and OCT-derived measurements.
  • The DL model's predictions were compared to those of two glaucoma specialists.

Main Results:

  • The DL model achieved an AUC of 0.839 and accuracy of 76.0% in predicting glaucoma progression.
  • The model significantly outperformed clinical graders (p<0.001).
  • Performance was consistent on a validation cohort and for predicting rapid progression.

Conclusions:

  • A novel DL model effectively integrates multimodal data for glaucoma progression prediction.
  • The model provides clinically relevant prognostic information, surpassing human expert accuracy.
  • This tool holds potential for improving glaucoma diagnostics and patient management.