AIMC Topic: Wet Macular Degeneration
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Clinically applicable deep learning-based decision aids for treatment of neovascular AMD.
Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Jan 22, 2022
PURPOSE: Anti-vascular endothelial growth factor (Anti-VEGF) therapy is currently seen as the standard for treatment of neovascular AMD (nAMD). However, while treatments are highly effective, decisions for initial treatment and retreatment are often ...
Machine Learning Can Predict Anti-VEGF Treatment Demand in a Treat-and-Extend Regimen for Patients with Neovascular AMD, DME, and RVO Associated Macular Edema.
Ophthalmology. Retina
May 8, 2021
PURPOSE: To assess the potential of machine learning to predict low and high treatment demand in real life in patients with neovascular age-related macular degeneration (nAMD), retinal vein occlusion (RVO), and diabetic macular edema (DME) treated ac...
Intravitreal Injections
Ranibizumab
Wet Macular Degeneration
Retinal Vein Occlusion
Angiogenesis Inhibitors
Machine Learning
Follow-Up Studies
Prognosis
Humans
Macular Edema
Retrospective Studies
Diabetic Retinopathy
Vascular Endothelial Growth Factor A
Female
Aged
Aged, 80 and over
Male
Middle Aged
AI-based structure-function correlation in age-related macular degeneration.
Eye (London, England)
Mar 25, 2021
Sensitive and robust outcome measures of retinal function are pivotal for clinical trials in age-related macular degeneration (AMD). A recent development is the implementation of artificial intelligence (AI) to infer results of psychophysical examina...
Predicting Incremental and Future Visual Change in Neovascular Age-Related Macular Degeneration Using Deep Learning.
Ophthalmology. Retina
Jan 28, 2021
PURPOSE: To evaluate the predictive usefulness of quantitative imaging biomarkers, acquired automatically from OCT scans, of cross-sectional and future visual outcomes of patients with neovascular age-related macular degeneration (AMD) starting anti-...
Humans
Prognosis
Tomography, Optical Coherence
Retrospective Studies
Deep Learning
Female
Vascular Endothelial Growth Factor A
Angiogenesis Inhibitors
Aged
Intravitreal Injections
Wet Macular Degeneration
Follow-Up Studies
Ranibizumab
Visual Acuity
Aged, 80 and over
Cross-Sectional Studies
Male
Middle Aged
Quantification of Key Retinal Features in Early and Late Age-Related Macular Degeneration Using Deep Learning.
American journal of ophthalmology
Jan 8, 2021
PURPOSE: We sought to develop and validate a deep learning model for segmentation of 13 features associated with neovascular and atrophic age-related macular degeneration (AMD).
Receptors, Vascular Endothelial Growth Factor
Retinal Drusen
Choroidal Neovascularization
Geographic Atrophy
Models, Statistical
Visual Acuity
Tomography, Optical Coherence
Vascular Endothelial Growth Factor A
Intravitreal Injections
Recombinant Fusion Proteins
Ranibizumab
Wet Macular Degeneration
Middle Aged
Deep Learning
ROC Curve
Angiogenesis Inhibitors
Aged
Aged, 80 and over
Sensitivity and Specificity
Male
Humans
Neural Networks, Computer
Female
Impact of macular fluid volume fluctuations on visual acuity during anti-VEGF therapy in eyes with nAMD.
Eye (London, England)
Jan 7, 2021
OBJECTIVES: To study the effect of repeated retinal thickness fluctuations during the anti-VEGF therapy maintenance phase in neovascular age-related macular degeneration (nAMD).
Generative adversarial networks to predict treatment response for neovascular age-related macular degeneration: interesting, but is it useful?
The British journal of ophthalmology
Aug 29, 2020
Automated diagnoses of age-related macular degeneration and polypoidal choroidal vasculopathy using bi-modal deep convolutional neural networks.
The British journal of ophthalmology
Jun 4, 2020
AIMS: To investigate the efficacy of a bi-modality deep convolutional neural network (DCNN) framework to categorise age-related macular degeneration (AMD) and polypoidal choroidal vasculopathy (PCV) from colour fundus images and optical coherence tom...
Predicting conversion to wet age-related macular degeneration using deep learning.
Nature medicine
May 18, 2020
Progression to exudative 'wet' age-related macular degeneration (exAMD) is a major cause of visual deterioration. In patients diagnosed with exAMD in one eye, we introduce an artificial intelligence (AI) system to predict progression to exAMD in the ...
Artificial Intelligence to Stratify Severity of Age-Related Macular Degeneration (AMD) and Predict Risk of Progression to Late AMD.
Translational vision science & technology
Apr 24, 2020
PURPOSE: To build and validate artificial intelligence (AI)-based models for AMD screening and for predicting late dry and wet AMD progression within 1 and 2 years.
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