AIMC Topic: Diabetic Retinopathy
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Optimizing diabetic retinopathy detection with electric fish algorithm and bilinear convolutional networks.
Scientific reports
Apr 23, 2025
Diabetic Retinopathy (DR) is a leading cause of vision impairment globally, necessitating regular screenings to prevent its progression to severe stages. Manual diagnosis is labor-intensive and prone to inaccuracies, highlighting the need for automat...
The association of trimethylamine N-oxide with diabetic retinopathy Pathology: Insights from network toxicology and molecular docking analysis.
Experimental eye research
Apr 22, 2025
Trimethylamine N-oxide (TMAO), a gut microbiota-derived metabolite, has emerged as a potential contributor to diabetic retinopathy (DR) progression. However, its molecular mechanisms in DR remain unclear. This study integrates network toxicology and ...
Diabetic retinopathy detection based on mobile maxout network and weber local descriptor feature selection using retinal fundus image.
Scientific reports
Apr 22, 2025
Retinal screening provides for earlier detection of diabetic retinopathy (DR) as well as prompt diagnosis. Recognizing DR utilizing color fundus imaging needs qualified specialists to know about the presence and significance of a few insignificant fe...
Sharper insights: Adaptive ellipse-template for robust fovea localization in challenging retinal landscapes.
Computers in biology and medicine
Apr 20, 2025
Automated identification of retinal landmarks, particularly the fovea is crucial for diagnosing diabetic retinopathy and other ocular diseases. But accurate identification is challenging due to varying contrast, color irregularities, anatomical struc...
Unsupervised machine learning analysis of optical coherence tomography radiomics features for predicting treatment outcomes in diabetic macular edema.
Scientific reports
Apr 18, 2025
This study aimed to identify distinct clusters of diabetic macular edema (DME) patients with differential anti-vascular endothelial growth factor (VEGF) treatment outcomes using an unsupervised machine learning (ML) approach based on radiomic feature...
Vascular Endothelial Growth Factor A
Diabetic Retinopathy
Retrospective Studies
Aged
Radiomics
Female
Humans
Unsupervised Machine Learning
Visual Acuity
Tomography, Optical Coherence
Macular Edema
Principal Component Analysis
Angiogenesis Inhibitors
Male
Middle Aged
Treatment Outcome
Cluster Analysis
Detection of diabetic macular oedema patterns with fine-grained image categorisation on optical coherence tomography.
BMJ open ophthalmology
Apr 15, 2025
PURPOSE: To develop an artificial intelligence (AI) system for detecting pathological patterns of diabetic macular oedema (DME) with fine-grained image categorisation using optical coherence tomography (OCT) images.
Acceptability, applicability, and cost-utility of artificial-intelligence-powered low-cost portable fundus camera for diabetic retinopathy screening in primary health care settings.
Diabetes research and clinical practice
Apr 5, 2025
AIMS: To evaluate the acceptability, applicability, and cost-utility of AI-powered portable fundus cameras for diabetic retinopathy (DR) screening in Hong Kong, providing a viable alternative screening solution for resource-limited areas.
Generating evidence to support the role of AI in diabetic eye screening: considerations from the UK National Screening Committee.
The Lancet. Digital health
Apr 3, 2025
Screening for diabetic retinopathy has been shown to reduce the risk of sight loss in people with diabetes, because of early detection and treatment of sight-threatening disease. There is long-standing interest in the possibility of automating parts ...
VisionGuard: enhancing diabetic retinopathy detection with hybrid deep learning.
Expert review of medical devices
Mar 30, 2025
OBJECTIVES: Early detection of diabetic retinopathy (DR) and timely intervention are critical for preventing vision loss. Recently, deep learning techniques have shown promising results in streamlining this process. The objective of this study was to...
Hybrid deep learning framework for diabetic retinopathy classification with optimized attention AlexNet.
Computers in biology and medicine
Mar 27, 2025
Diabetic retinopathy (DR) is a chronic condition associated with diabetes that can lead to vision impairment and, if not addressed, may progress to irreversible blindness. Consequently, it is essential to detect pathological changes in the retina to ...
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