AIMC Topic: Macular Degeneration
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Artificial intelligence classification model for macular degeneration images: a robust optimization framework for residual neural networks.
BMC bioinformatics
Nov 8, 2021
BACKGROUND: The prevalence of chronic disease is growing in aging societies, and artificial-intelligence-assisted interpretation of macular degeneration images is a topic that merits research. This study proposes a residual neural network (ResNet) mo...
Imaging and artificial intelligence for progression of age-related macular degeneration.
Experimental biology and medicine (Maywood, N.J.)
Aug 18, 2021
Age-related macular degeneration (AMD) is a leading cause of severe vision loss. With our aging population, it may affect 288 million people globally by the year 2040. AMD progresses from an early and intermediate dry form to an advanced one, which m...
Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks.
Nature communications
Aug 10, 2021
Retinal fundus diseases can lead to irreversible visual impairment without timely diagnoses and appropriate treatments. Single disease-based deep learning algorithms had been developed for the detection of diabetic retinopathy, age-related macular de...
Attention-based deep learning system for automated diagnoses of age-related macular degeneration in optical coherence tomography images.
Medical physics
Aug 9, 2021
PURPOSE: The progression of age-related macular degeneration (AMD) is critical to treatment decisions in clinical practice. The disease can be classified into four categories namely, drusen, inactive choroidal neovascularization (CNV), active CNV, an...
Diagnosis of retinal disorders from Optical Coherence Tomography images using CNN.
PloS one
Jul 27, 2021
An efficient automatic decision support system for detection of retinal disorders is important and is the need of the hour. Optical Coherence Tomography (OCT) is the current imaging modality for the early detection of retinal disorders non-invasively...
Self-Supervised Feature Learning and Phenotyping for Assessing Age-Related Macular Degeneration Using Retinal Fundus Images.
Ophthalmology. Retina
Jul 2, 2021
OBJECTIVE: Diseases such as age-related macular degeneration (AMD) are classified based on human rubrics that are prone to bias. Supervised neural networks trained using human-generated labels require labor-intensive annotations and are restricted to...
Multimodal deep learning with feature level fusion for identification of choroidal neovascularization activity in age-related macular degeneration.
Acta ophthalmologica
Jun 23, 2021
PURPOSE: This study aimed to determine the efficacy of a multimodal deep learning (DL) model using optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) images for the assessment of choroidal neovascularization (CNV) ...
A column-based deep learning method for the detection and quantification of atrophy associated with AMD in OCT scans.
Medical image analysis
Jun 12, 2021
The objective quantification of retinal atrophy associated with age-related macular degeneration (AMD) is required for clinical diagnosis, follow-up, treatment efficacy evaluation, and clinical research. Spectral Domain Optical Coherence Tomography (...
Detection of oedema on optical coherence tomography images using deep learning model trained on noisy clinical data.
Acta ophthalmologica
May 15, 2021
PURPOSE: To meet the demands imposed by the continuing growth of the Age-related macular degeneration (AMD) patient population, automation of follow-ups by detecting retinal oedema using deep learning might be a viable approach. However, preparing an...
Diagnostic accuracy of current machine learning classifiers for age-related macular degeneration: a systematic review and meta-analysis.
Eye (London, England)
May 6, 2021
BACKGROUND AND OBJECTIVE: The objective of this study was to systematically review and meta-analyze the diagnostic accuracy of current machine learning classifiers for age-related macular degeneration (AMD). Artificial intelligence diagnostic algorit...
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