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Related Concept Videos

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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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Related Experiment Video

Updated: Apr 17, 2026

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential
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Applying "Lasso" Regression to Predict Future Visual Field Progression in Glaucoma Patients.

Yuri Fujino, Hiroshi Murata, Chihiro Mayama

    Investigative Ophthalmology & Visual Science
    |February 21, 2015
    PubMed
    Summary

    Lasso regression accurately predicts glaucoma visual field progression, outperforming traditional methods, especially with limited patient data. This offers a more precise approach to monitoring disease advancement.

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    Area of Science:

    • Ophthalmology
    • Medical Statistics
    • Data Science

    Background:

    • Glaucoma is a progressive optic neuropathy leading to irreversible vision loss.
    • Accurate prediction of visual field (VF) progression is crucial for timely treatment adjustments in glaucoma management.
    • Traditional regression models may have limitations in predicting VF changes with limited data.

    Purpose of the Study:

    • To evaluate the predictive performance of various regression models, including Lasso regression, for future visual field (VF) progression in glaucoma patients.
    • To compare the accuracy of different regression techniques in predicting the mean total deviation (mTD) of a future VF.

    Main Methods:

    • Utilized 10 VFs from 513 eyes of 324 open-angle glaucoma patients over approximately 4.9 years.
    • Applied ordinary least squares linear regression (OLSLR), M-robust, MM-robust, Skipped, Deepest, and Lasso regression to predict the mTD of the 10th VF.
    • Varied the number of prior VFs used for prediction, from the first three to all previous VFs.

    Main Results:

    • OLSLR showed significant prediction errors, particularly with fewer VFs (5.7 ± 6.1 dB with 3 VFs).
    • M-robust, MM-robust, Skipped, and Deepest regressions did not significantly improve prediction accuracy over OLSLR in most cases.
    • Lasso regression demonstrated significantly smaller prediction errors, even with a limited number of VFs (2.0 ± 2.2 dB with 3 VFs), matching the accuracy of OLSLR with all prior VFs (1.2 ± 1.1 dB).

    Conclusions:

    • Ordinary least squares linear regression yields substantial prediction errors when based on a small number of visual fields.
    • Lasso regression provides substantially more accurate predictions of glaucoma visual field progression, particularly when utilizing limited historical VF data.
    • Lasso regression represents a valuable tool for enhancing the precision of glaucoma progression monitoring.