AI Medical Compendium Journal:
Ophthalmology

Showing 31 to 40 of 49 articles

A Deep Learning Approach for Automated Detection of Geographic Atrophy from Color Fundus Photographs.

Ophthalmology Jun 11, 2019
PURPOSE: To assess the utility of deep learning in the detection of geographic atrophy (GA) from color fundus photographs and to explore potential utility in detecting central GA (CGA).
Reproducibility of Results Aged Aged, 80 and over Sensitivity and Specificity Humans Female Area Under Curve Diagnostic Techniques, Ophthalmological Photography Physical Examination Geographic Atrophy Male Middle Aged Deep Learning Image Processing, Computer-Assisted
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Development and Validation of Deep Learning Models for Screening Multiple Abnormal Findings in Retinal Fundus Images.

Ophthalmology May 31, 2019
PURPOSE: To develop and evaluate deep learning models that screen multiple abnormal findings in retinal fundus images.
Sensitivity and Specificity Datasets as Topic Cross-Sectional Studies Retinal Diseases Male Middle Aged Area Under Curve Fundus Oculi Image Interpretation, Computer-Assisted Deep Learning ROC Curve Female Aged Aged, 80 and over Adult Humans Neural Networks, Computer Machine Learning Algorithms
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From Machine to Machine: An OCT-Trained Deep Learning Algorithm for Objective Quantification of Glaucomatous Damage in Fundus Photographs.

Ophthalmology Dec 20, 2018
PURPOSE: Previous approaches using deep learning (DL) algorithms to classify glaucomatous damage on fundus photographs have been limited by the requirement for human labeling of a reference training set. We propose a new approach using quantitative s...
Photography Glaucoma, Open-Angle Tonometry, Ocular Gonioscopy Tomography, Optical Coherence Fundus Oculi Nerve Fibers Optic Disk Retinal Ganglion Cells Visual Fields Visual Field Tests Optic Nerve Diseases Middle Aged Deep Learning Algorithms ROC Curve Female Visual Acuity Aged Aged, 80 and over Humans Cross-Sectional Studies Intraocular Pressure Male
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Using a Deep Learning Algorithm and Integrated Gradients Explanation to Assist Grading for Diabetic Retinopathy.

Ophthalmology Dec 13, 2018
PURPOSE: To understand the impact of deep learning diabetic retinopathy (DR) algorithms on physician readers in computer-assisted settings.
Humans Diabetic Retinopathy Algorithms Female Deep Learning ROC Curve Reference Standards Photography Ophthalmologists Reproducibility of Results Sensitivity and Specificity Male Diagnosis, Computer-Assisted
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DeepSeeNet: A Deep Learning Model for Automated Classification of Patient-based Age-related Macular Degeneration Severity from Color Fundus Photographs.

Ophthalmology Nov 22, 2018
PURPOSE: In assessing the severity of age-related macular degeneration (AMD), the Age-Related Eye Disease Study (AREDS) Simplified Severity Scale predicts the risk of progression to late AMD. However, its manual use requires the time-consuming partic...
Humans Prospective Studies Female Reproducibility of Results Risk Factors Aged Aged, 80 and over Area Under Curve Severity of Illness Index Diagnostic Techniques, Ophthalmological Geographic Atrophy Sensitivity and Specificity Diagnosis, Computer-Assisted Photography Male Deep Learning Retinal Drusen Middle Aged Models, Theoretical Disease Progression
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Reply.

Ophthalmology Oct 19, 2018
Machine Learning
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Re: Lee et al.: Machine learning has arrived! (Ophthalmology. 2017;124:1726-1728).

Ophthalmology Oct 19, 2018
Ophthalmology Machine Learning
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A Deep Learning Algorithm for Prediction of Age-Related Eye Disease Study Severity Scale for Age-Related Macular Degeneration from Color Fundus Photography.

Ophthalmology Apr 10, 2018
PURPOSE: Age-related macular degeneration (AMD) is a common threat to vision. While classification of disease stages is critical to understanding disease risk and progression, several systems based on color fundus photographs are known. Most of these...
Macula Lutea Aged Cross-Sectional Studies Photography Deep Learning Male Middle Aged Fundus Oculi Severity of Illness Index Humans Macular Degeneration Algorithms Diagnostic Techniques, Ophthalmological Female Reproducibility of Results
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Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathy.

Ophthalmology Mar 13, 2018
PURPOSE: Use adjudication to quantify errors in diabetic retinopathy (DR) grading based on individual graders and majority decision, and to train an improved automated algorithm for DR grading.
Clinical Competence Ophthalmologists Retrospective Studies Humans ROC Curve Female Diabetic Retinopathy Mass Screening Male Machine Learning Reference Standards Middle Aged Algorithms
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Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.

Ophthalmology Mar 2, 2018
PURPOSE: To assess the performance of a deep learning algorithm for detecting referable glaucomatous optic neuropathy (GON) based on color fundus photographs.
Retrospective Studies Humans Deep Learning Optic Disk Glaucoma ROC Curve Optic Nerve Diseases Algorithms Fundus Oculi Diagnostic Techniques, Ophthalmological Photography
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