AIMC Topic: Glaucoma, Open-Angle

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Assessing Glaucoma Progression Using Machine Learning Trained on Longitudinal Visual Field and Clinical Data.

Ophthalmology Dec 25, 2020
PURPOSE: Rule-based approaches to determining glaucoma progression from visual fields (VFs) alone are discordant and have tradeoffs. To detect better when glaucoma progression is occurring, we used a longitudinal data set of merged VF and clinical da...
Humans Glaucoma Machine Learning Algorithms Retrospective Studies Visual Fields Ophthalmologists Glaucoma, Open-Angle Clinical Competence Female ROC Curve Aged Follow-Up Studies Intraocular Pressure Male Disease Progression
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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 Nov 4, 2020
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...
Retina Diagnostic Techniques, Ophthalmological Glaucoma, Open-Angle Bruch Membrane Low Tension Glaucoma Humans Image Processing, Computer-Assisted Middle Aged Female Deep Learning Area Under Curve Adult ROC Curve Tomography, Optical Coherence Intraocular Pressure Male
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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.
Deep Learning Tomography, Optical Coherence Double-Blind Method Humans 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...
Linear Models Visual Field Tests Eye Glaucoma, Open-Angle Female Reproducibility of Results Adult Sensitivity and Specificity Intraocular Pressure Male Middle Aged Disease Progression Deep Learning Visual Fields Humans
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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.
Retrospective Studies Female Aged Adult Sensitivity and Specificity Humans Visual Acuity Vision Disorders Tomography, Optical Coherence Visual Fields Visual Field Tests Optic Nerve Diseases Cross-Sectional Studies Intraocular Pressure Male Middle Aged Deep Learning Glaucoma, Open-Angle Gonioscopy Slit Lamp Microscopy Axial Length, Eye
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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.
Optic Disk Retinal Ganglion Cells Visual Fields Glaucoma, Open-Angle Middle Aged Deep Learning Structure-Activity Relationship Tomography, Optical Coherence Nerve Fibers Cross-Sectional Studies Intraocular Pressure Humans Male Female
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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.
Smartphone Glaucoma, Open-Angle Adult Ocular Hypertension Humans Low Tension Glaucoma Intraocular Pressure Machine Learning Glaucoma, Angle-Closure Male Tonometry, Ocular Middle Aged Female Pilot Projects Reproducibility of Results Aged
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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.
Fundus Oculi Nerve Fibers Retinal Ganglion Cells Visual Fields Visual Field Tests Optic Nerve Diseases Photography Physical Examination Glaucoma, Open-Angle Gonioscopy Deep Learning ROC Curve Vision Disorders Area Under Curve Tomography, Optical Coherence Humans Aged Cross-Sectional Studies Intraocular Pressure Male Algorithms Middle Aged Retrospective Studies Female
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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...
Deep Learning ROC Curve Humans Area Under Curve Glaucoma, Open-Angle Female Referral and Consultation Nerve Fibers Retrospective Studies Specialization Aged Datasets as Topic Optic Disk Sensitivity and Specificity Retinal Ganglion Cells Optic Nerve Diseases Male Ophthalmologists Middle Aged
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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).
Male Reproducibility of Results Odds Ratio Middle Aged Aged Humans Disease Progression Glaucoma, Open-Angle Aged, 80 and over Machine Learning ROC Curve Filtering Surgery Sensitivity and Specificity Retrospective Studies Models, Statistical Intraocular Pressure Electronic Health Records Female
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