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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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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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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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Ophthalmic drug delivery faces major limitations due to poor absorption across the corneal membrane. This process is primarily driven by diffusion and is influenced by two main factors: the physicochemical properties of the drug and tear drainage. Most ophthalmic drugs, such as pilocarpine, epinephrine, atropine, and local anesthetics, are weak bases. They are typically formulated at an acidic pH to enhance chemical stability. However, this leads to high ionization, reducing their ability to...
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Updated: Mar 27, 2026

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Predicting Intraocular Pressure From Glaucoma Patients Receiving Medication Treatment Using Explainable Machine

Robert T James1, Wenke Liu2, Gadi Wollstein1,3,4

  • 1Departments of Ophthalmology and Radiology, Tech4Health Institute and Neuroscience Institute, New York University Grossman School of Medicine, NYU Langone Health, New York University, New York, New York, USA, nyu.edu.

Biomed Research International
|March 25, 2026
PubMed
Summary
This summary is machine-generated.

Explainable AI predicts glaucoma treatment success by analyzing patient data. Key factors like Insulin-like Growth Factor 1 and LDL cholesterol influence intraocular pressure outcomes.

Keywords:
explainable machine learningglaucomainsulin-like growth factor 1 (IGF-1)intraocular pressure (IOP)low-density lipoprotein (LDL)

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Area of Science:

  • Ophthalmology
  • Medical Informatics
  • Computational Biology

Background:

  • Glaucoma is a neurodegenerative disease impacting vision, with treatment aiming to reduce intraocular pressure (IOP).
  • Some patients do not respond effectively to IOP-lowering treatments, risking progressive vision loss.
  • Explainable machine learning (EML) offers tools for predicting treatment outcomes and identifying influential factors.

Purpose of the Study:

  • To utilize EML to predict IOP in glaucoma patients undergoing medication treatment.
  • To identify key features impacting treatment success using EML.

Main Methods:

  • The study analyzed data from 161 glaucoma patients in the UK Biobank.
  • eXtreme Gradient Boosting (XGBoost) was employed for predicting IOP, with feature sets including demographics, physiometabolic data, and medications.
  • SHapley Additive exPlanation (SHAP) values were calculated to determine feature importance and interactions.

Main Results:

  • XGBoost achieved an AUC of 0.708 when using a combined feature set.
  • Insulin-like Growth Factor 1 (IGF-1), low-density lipoprotein (LDL), and lymphocyte count were the most significant predictors of IOP.
  • Strong interactions were observed between LDL and IGF-1 in influencing treatment outcomes.

Conclusions:

  • EML, specifically XGBoost, can effectively predict IOP outcomes in glaucoma patients.
  • Blood levels of LDL and IGF-1 are crucial factors influencing the effectiveness of IOP-lowering treatments.
  • This approach aids in understanding individual prognoses and identifying potential therapeutic targets.