AIMC Topic: Glaucoma, Open-Angle

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Hybrid Deep Learning on Single Wide-field Optical Coherence tomography Scans Accurately Classifies Glaucoma Suspects.

Journal of glaucoma Dec 1, 2017
PURPOSE: Existing summary statistics based upon optical coherence tomographic (OCT) scans and/or visual fields (VFs) are suboptimal for distinguishing between healthy and glaucomatous eyes in the clinic. This study evaluates the extent to which a hyb...
Humans Neural Networks, Computer Machine Learning Reproducibility of Results Intraocular Pressure Tomography, Optical Coherence Nerve Fibers Retinal Ganglion Cells Visual Fields Glaucoma, Open-Angle Ocular Hypertension
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Artificial Neural Network Approach for Differentiating Open-Angle Glaucoma From Glaucoma Suspect Without a Visual Field Test.

Investigative ophthalmology & visual science Jun 1, 2015
PURPOSE: To increase the effectiveness of treating open-angle glaucoma (OAG), we tried to find a screening method of differentiating OAG from glaucoma suspect (GS) without a visual field (VF) test.
Humans Neural Networks, Computer Glaucoma Female Risk Factors Aged Adult Sensitivity and Specificity Cross-Sectional Studies Intraocular Pressure Male Middle Aged Refractive Errors Visual Acuity Diagnosis, Differential Predictive Value of Tests Tomography, Optical Coherence Nerve Fibers Retinal Ganglion Cells Multivariate Analysis Diagnostic Techniques, Ophthalmological Glaucoma, Open-Angle Ocular Hypertension
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