AIMC Topic: Visual Fields

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Treatment Potential for Macular Cone Vision in Leber Congenital Amaurosis Due to CEP290 or NPHP5 Mutations: Predictions From Artificial Intelligence.

Investigative ophthalmology & visual science Jun 3, 2019
PURPOSE: To use supervised machine learning to predict visual function from retinal structure in retinitis pigmentosa (RP) and apply these estimates to CEP290- and NPHP5-associated Leber congenital amaurosis (LCA) to determine the potential for funct...
Mutation Visual Fields Visual Field Tests Cytoskeletal Proteins Antigens, Neoplasm Neoplasm Proteins Tomography, Optical Coherence Retinal Cone Photoreceptor Cells Genetic Therapy Calmodulin-Binding Proteins Cell Cycle Proteins Color Vision Defects Leber Congenital Amaurosis Retinitis Pigmentosa Machine Learning Female Young Adult Humans Middle Aged Adolescent Adult Male
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Neural population control via deep image synthesis.

Science (New York, N.Y.) May 3, 2019
Particular deep artificial neural networks (ANNs) are today's most accurate models of the primate brain's ventral visual stream. Using an ANN-driven image synthesis method, we found that luminous power patterns (i.e., images) can be applied to primat...
Neural Networks, Computer Animals Nerve Net Models, Neurological Visual Cortex Macaca Neurons Visual Fields
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Artificial intelligence in glaucoma.

Current opinion in ophthalmology Mar 1, 2019
PURPOSE OF REVIEW: The use of computers has become increasingly relevant to medical decision-making, and artificial intelligence methods have recently demonstrated significant advances in medicine. We therefore provide an overview of current artifici...
Humans Glaucoma Visual Fields Diagnostic Techniques, Ophthalmological Artificial Intelligence Diagnosis, Computer-Assisted Tomography, Optical Coherence
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An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis.

Investigative ophthalmology & visual science Jan 2, 2019
PURPOSE: To detect visual field (VF) progression by analyzing spatial pattern changes.
False Positive Reactions Spatial Processing Predictive Value of Tests Visual Fields Visual Field Tests Glaucoma Artificial Intelligence Disease Progression Follow-Up Studies Vision Disorders Diagnosis, Computer-Assisted Cohort Studies Humans
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Deep-learning Classifier With an Ultrawide-field Scanning Laser Ophthalmoscope Detects Glaucoma Visual Field Severity.

Journal of glaucoma Jul 1, 2018
PURPOSE: To evaluate the accuracy of detecting glaucoma visual field defect severity using deep-learning (DL) classifier with an ultrawide-field scanning laser ophthalmoscope.
Visual Field Tests Ophthalmoscopes Vision Disorders Image Interpretation, Computer-Assisted Humans Visual Fields Deep Learning Reproducibility of Results Cross-Sectional Studies Glaucoma Microscopy, Confocal Aged Adult Retrospective Studies Middle Aged Intraocular Pressure Sensitivity and Specificity Female Severity of Illness Index Male
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Deep Learning for Predicting Refractive Error From Retinal Fundus Images.

Investigative ophthalmology & visual science Jun 1, 2018
PURPOSE: We evaluate how deep learning can be applied to extract novel information such as refractive error from retinal fundus imaging.
Deep Learning Fundus Oculi Retina Vision Tests Datasets as Topic Visual Fields Male Humans Middle Aged Algorithms Refraction, Ocular Refractive Errors Female Aged Adult
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A Deep Learning Approach to Digitally Stain Optical Coherence Tomography Images of the Optic Nerve Head.

Investigative ophthalmology & visual science Jan 1, 2018
PURPOSE: To develop a deep learning approach to digitally stain optical coherence tomography (OCT) images of the optic nerve head (ONH).
Reproducibility of Results Adult Male Middle Aged Machine Learning Humans Algorithms Female Glaucoma Retinal Ganglion Cells Tomography, Optical Coherence Visual Fields Nerve Fibers Optic Disk
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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...
Nerve Fibers Retinal Ganglion Cells Visual Fields Glaucoma, Open-Angle Reproducibility of Results Ocular Hypertension Humans Intraocular Pressure Neural Networks, Computer Tomography, Optical Coherence Machine Learning
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