AI Medical Compendium Journal:
Ophthalmology

Showing 21 to 30 of 49 articles

Deep Learning Automated Detection of Reticular Pseudodrusen from Fundus Autofluorescence Images or Color Fundus Photographs in AREDS2.

Ophthalmology May 21, 2020
PURPOSE: To develop deep learning models for detecting reticular pseudodrusen (RPD) using fundus autofluorescence (FAF) images or, alternatively, color fundus photographs (CFP) in the context of age-related macular degeneration (AMD).
Reproducibility of Results Aged Aged, 80 and over Sensitivity and Specificity Male Humans Female Datasets as Topic Optical Imaging Fluorescein Angiography Ophthalmologists Retinal Drusen Middle Aged Deep Learning ROC Curve Area Under Curve Macular Degeneration
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Using Deep Learning to Automate Goldmann Applanation Tonometry Readings.

Ophthalmology Apr 25, 2020
PURPOSE: To develop an objective and automated method for measuring intraocular pressure using deep learning and fixed-force Goldmann applanation tonometry (GAT) techniques.
Humans Glaucoma Prospective Studies Intraocular Pressure Male Middle Aged Deep Learning ROC Curve Female Reproducibility of Results Aged Cross-Sectional Studies Tonometry, Ocular
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Monitoring Glaucomatous Functional Loss Using an Artificial Intelligence-Enabled Dashboard.

Ophthalmology Mar 10, 2020
PURPOSE: To develop an artificial intelligence (AI) dashboard for monitoring glaucomatous functional loss.
False Negative Reactions Optic Nerve Diseases Cross-Sectional Studies Retrospective Studies Monitoring, Physiologic Male Visual Acuity Middle Aged Female Longitudinal Studies Humans Vision Disorders Aged Glaucoma Predictive Value of Tests Adult Artificial Intelligence Visual Fields Sensitivity and Specificity
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A Deep Learning Model for Segmentation of Geographic Atrophy to Study Its Long-Term Natural History.

Ophthalmology Feb 15, 2020
PURPOSE: To develop and validate a deep learning model for the automatic segmentation of geographic atrophy (GA) using color fundus images (CFIs) and its application to study the growth rate of GA.
Fluorescein Angiography Geographic Atrophy Deep Learning Follow-Up Studies Fundus Oculi Retina Humans Forecasting Prospective Studies Female Aged Male Disease Progression Severity of Illness Index
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Beyond Performance Metrics: Automatic Deep Learning Retinal OCT Analysis Reproduces Clinical Trial Outcome.

Ophthalmology Dec 23, 2019
PURPOSE: To validate the efficacy of a fully automatic, deep learning-based segmentation algorithm beyond conventional performance metrics by measuring the primary outcome of a clinical trial for macular telangiectasia type 2 (MacTel2).
Retinal Photoreceptor Cell Outer Segment Ciliary Neurotrophic Factor Retinal Vessels Retinal Telangiectasis Drug Implants Humans Retinal Photoreceptor Cell Inner Segment Female Tomography, Optical Coherence Reproducibility of Results Visual Fields Male Visual Field Tests Deep Learning Fluorescein Angiography Treatment Outcome Visual Acuity
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Artificial Intelligence Classification of Central Visual Field Patterns in Glaucoma.

Ophthalmology Dec 12, 2019
PURPOSE: To quantify the central visual field (VF) loss patterns in glaucoma using artificial intelligence.
Middle Aged Humans Visual Field Tests Female Vision Disorders Glaucoma Aged Bayes Theorem Artificial Intelligence Cross-Sectional Studies Visual Fields Retrospective Studies Intraocular Pressure Male
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Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps.

Ophthalmology Sep 30, 2019
PURPOSE: To develop and evaluate a deep learning system for differentiating between eyes with and without glaucomatous visual field damage (GVFD) and predicting the severity of GFVD from spectral domain OCT (SD OCT) optic nerve head images.
Glaucoma Female Aged Adult Optic Nerve Diseases Male Nerve Fibers Diagnostic Techniques, Ophthalmological Optic Disk Humans Retinal Ganglion Cells Middle Aged Visual Fields Deep Learning Visual Field Tests Vision Disorders Predictive Value of Tests
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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 Male Middle Aged Datasets as Topic Nerve Fibers Optic Disk Deep Learning Retinal Ganglion Cells Ophthalmologists ROC Curve Optic Nerve Diseases Glaucoma, Open-Angle Area Under Curve Specialization Referral and Consultation
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An Ophthalmologist's Guide to Deciphering Studies in Artificial Intelligence.

Ophthalmology Sep 21, 2019
Reference Standards Ophthalmologists Artificial Intelligence Biomedical Research Image Processing, Computer-Assisted Peer Review, Research Eye Diseases Humans Neural Networks, Computer
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Natural Language Processing to Quantify Microbial Keratitis Measurements.

Ophthalmology Jun 11, 2019
A natural language processing (NLP) algorithm to extract microbial keratitis morphology measurements from the electronic health record (EHR) was 75-96% sensitive and 91%-96% specific. NLP accurately extracts data from the corneal exam free-text EHR f...
Natural Language Processing Eye Infections, Bacterial Corneal Ulcer Humans Electronic Health Records Reproducibility of Results Sensitivity and Specificity
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