AIMC Topic: Glaucoma, Open-Angle

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OCT Signal Enhancement with Deep Learning.

Ophthalmology. Glaucoma Oct 15, 2020
PURPOSE: To establish whether deep learning methods are able to improve the signal-to-noise ratio of time-domain (TD) OCT images to approach that of spectral-domain (SD) OCT images.
Humans Deep Learning Tomography, Optical Coherence Double-Blind Method Bayes Theorem Glaucoma, Open-Angle
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The usefulness of the Deep Learning method of variational autoencoder to reduce measurement noise in glaucomatous visual fields.

Scientific reports May 12, 2020
The aim of the study was to investigate the usefulness of processing visual field (VF) using a variational autoencoder (VAE). The training data consisted of 82,433 VFs from 16,836 eyes. Testing dataset 1 consisted of test-retest VFs from 104 eyes wit...
Deep Learning Adult Visual Fields Glaucoma, Open-Angle Humans Linear Models Sensitivity and Specificity Visual Field Tests Intraocular Pressure Female Eye Male Reproducibility of Results Middle Aged Disease Progression
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Predicting the Glaucomatous Central 10-Degree Visual Field From Optical Coherence Tomography Using Deep Learning and Tensor Regression.

American journal of ophthalmology May 6, 2020
PURPOSE: To predict the visual field (VF) of glaucoma patients within the central 10° from optical coherence tomography (OCT) measurements using deep learning and tensor regression.
Deep Learning Visual Acuity Vision Disorders Humans Tomography, Optical Coherence Retrospective Studies Optic Nerve Diseases Visual Fields Female Glaucoma, Open-Angle Visual Field Tests Aged Gonioscopy Sensitivity and Specificity Adult Slit Lamp Microscopy Cross-Sectional Studies Axial Length, Eye Intraocular Pressure Male Middle Aged
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Improving the Structure-Function Relationship in Glaucomatous Visual Fields by Using a Deep Learning-Based Noise Reduction Approach.

Ophthalmology. Glaucoma Jan 11, 2020
PURPOSE: To investigate whether processing visual field (VF) measurements using a variational autoencoder (VAE) improves the structure-function relationship in glaucoma.
Humans Deep Learning Structure-Activity Relationship Tomography, Optical Coherence Nerve Fibers Optic Disk Retinal Ganglion Cells Female Cross-Sectional Studies Intraocular Pressure Male Middle Aged Visual Fields Glaucoma, Open-Angle
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Development and validation of a machine learning, smartphone-based tonometer.

The British journal of ophthalmology Dec 23, 2019
BACKGROUND/AIMS: To compare intraocular pressure (IOP) measurements using a prototype smartphone tonometer with other tonometers used in clinical practice.
Glaucoma, Open-Angle Ocular Hypertension Glaucoma, Angle-Closure Tonometry, Ocular Low Tension Glaucoma Intraocular Pressure Male Middle Aged Pilot Projects Smartphone Humans Machine Learning Female Reproducibility of Results Aged Adult
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Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs.

American journal of ophthalmology Nov 12, 2019
PURPOSE: To compare the diagnostic performance of human gradings vs predictions provided by a machine-to-machine (M2M) deep learning (DL) algorithm trained to quantify retinal nerve fiber layer (RNFL) damage on fundus photographs.
Optic Nerve Diseases Photography Physical Examination Glaucoma, Open-Angle Gonioscopy Tomography, Optical Coherence Fundus Oculi Nerve Fibers Retinal Ganglion Cells Visual Fields Visual Field Tests Middle Aged Deep Learning ROC Curve Vision Disorders Humans Retrospective Studies Area Under Curve Algorithms Female Aged Cross-Sectional Studies Intraocular Pressure Male
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Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs.

Ophthalmology Sep 24, 2019
PURPOSE: To develop and validate a deep learning (DL) algorithm that predicts referable glaucomatous optic neuropathy (GON) and optic nerve head (ONH) features from color fundus images, to determine the relative importance of these features in referr...
Humans Retrospective Studies Female Aged Sensitivity and Specificity Ophthalmologists Glaucoma, Open-Angle Specialization Referral and Consultation Male Middle Aged Datasets as Topic Deep Learning Nerve Fibers ROC Curve Optic Disk Area Under Curve Retinal Ganglion Cells Optic Nerve Diseases
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Machine Learning-Based Predictive Modeling of Surgical Intervention in Glaucoma Using Systemic Data From Electronic Health Records.

American journal of ophthalmology Jul 16, 2019
PURPOSE: To predict the need for surgical intervention in patients with primary open-angle glaucoma (POAG) using systemic data in electronic health records (EHRs).
Electronic Health Records Female Reproducibility of Results Aged Models, Statistical Humans Aged, 80 and over Intraocular Pressure Odds Ratio Machine Learning Sensitivity and Specificity Male Glaucoma, Open-Angle Retrospective Studies Middle Aged Filtering Surgery Disease Progression ROC Curve
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Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study.

Eye (London, England) Jul 2, 2019
OBJECTIVES: To evaluate the performance of a deep learning based Artificial Intelligence (AI) software for detection of glaucoma from stereoscopic optic disc photographs, and to compare this performance to the performance of a large cohort of ophthal...
Optic Nerve Diseases False Positive Reactions Photography Ophthalmologists Glaucoma, Open-Angle Optometrists Clinical Competence ROC Curve Humans Europe Artificial Intelligence Predictive Value of Tests Retrospective Studies Observer Variation Optic Disk Reproducibility of Results Sensitivity and Specificity Diagnosis, Computer-Assisted Deep Learning
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A Deep Learning Algorithm to Quantify Neuroretinal Rim Loss From Optic Disc Photographs.

American journal of ophthalmology Jan 26, 2019
PURPOSE: To train a deep learning (DL) algorithm that quantifies glaucomatous neuroretinal damage on fundus photographs using the minimum rim width relative to Bruch membrane opening (BMO-MRW) from spectral-domain optical coherence tomography (SDOCT)...
Deep Learning Aged, 80 and over Optic Disk Glaucoma, Open-Angle Cross-Sectional Studies Humans Retinal Ganglion Cells Vision Disorders Bruch Membrane Algorithms Area Under Curve Visual Fields Intraocular Pressure Retrospective Studies Visual Field Tests Male Tomography, Optical Coherence Female Optic Nerve Diseases Nerve Fibers Middle Aged Aged Photography
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