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Low Tension Glaucoma

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Using Kalman Filtering to Forecast Disease Trajectory for Patients With Normal Tension Glaucoma.

American journal of ophthalmology 30336130
PURPOSE: To determine whether a machine learning technique called Kalman filtering (KF) can accurately forecast future values of mean deviation (MD), pattern standard deviation, and intraocular pressure for patients with normal tension glaucoma (NTG)...
Aged Algorithms Asian People Female Forecasting Humans Intraocular Pressure Japan Low Tension Glaucoma Machine Learning Male Middle Aged Retrospective Studies Visual Field Tests Visual Fields
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Development and validation of a machine learning, smartphone-based tonometer.

The British journal of ophthalmology 31871048
BACKGROUND/AIMS: To compare intraocular pressure (IOP) measurements using a prototype smartphone tonometer with other tonometers used in clinical practice.
Adult Aged Female Glaucoma, Angle-Closure Glaucoma, Open-Angle Humans Intraocular Pressure Low Tension Glaucoma Machine Learning Male Middle Aged Ocular Hypertension Pilot Projects Reproducibility of Results Smartphone Tonometry, Ocular
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Machine learning classifiers-based prediction of normal-tension glaucoma progression in young myopic patients.

Japanese journal of ophthalmology 31848786
PURPOSE: To assess the performance of machine learning classifiers for prediction of progression of normal-tension glaucoma (NTG) in young myopic patients.
Adult Area Under Curve Cross-Sectional Studies Diagnosis, Computer-Assisted Disease Progression Female Gonioscopy Humans Intraocular Pressure Low Tension Glaucoma Machine Learning Male Myopia Nerve Fibers Retinal Ganglion Cells ROC Curve Slit Lamp Microscopy Tomography, Optical Coherence Visual Field Tests Visual Fields Young Adult
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Deep learning classification of early normal-tension glaucoma and glaucoma suspects using Bruch's membrane opening-minimum rim width and RNFL.

Scientific reports 33149191
We aimed to classify early normal-tension glaucoma (NTG) and glaucoma suspect (GS) using Bruch's membrane opening-minimum rim width (BMO-MRW), peripapillary retinal nerve fiber layer (RNFL), and the color classification of RNFL based on a deep-learni...
Adult Area Under Curve Bruch Membrane Deep Learning Diagnostic Techniques, Ophthalmological Female Glaucoma, Open-Angle Humans Image Processing, Computer-Assisted Intraocular Pressure Low Tension Glaucoma Male Middle Aged Retina ROC Curve Tomography, Optical Coherence
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Deep-learning-based prediction of glaucoma conversion in normotensive glaucoma suspects.

The British journal of ophthalmology 37918891
BACKGROUND/AIMS: To assess the performance of deep-learning (DL) models for prediction of conversion to normal-tension glaucoma (NTG) in normotensive glaucoma suspect (GS) patients.
Aged Algorithms Blood Pressure Deep Learning Disease Progression Female Follow-Up Studies Humans Intraocular Pressure Low Tension Glaucoma Male Middle Aged Nerve Fibers Ocular Hypertension Optic Disk Retinal Ganglion Cells Retrospective Studies ROC Curve Tonometry, Ocular Visual Fields
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