AIMC Topic: Diabetic Retinopathy
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Transformer attention fusion for fine grained medical image classification.
Scientific reports
Jul 1, 2025
Fine-grained visual classification is fundamental for medical image applications because it detects minor lesions. Diabetic retinopathy (DR) is a preventable cause of blindness, which requires exact and timely diagnosis to prevent vision damage. The ...
Realistic fundus photograph generation for improving automated disease classification.
The British journal of ophthalmology
Jun 23, 2025
AIMS: This study aims to investigate whether denoising diffusion probabilistic models (DDPMs) could generate realistic retinal images, and if they could be used to improve the performance of a deep convolutional neural network (CNN) ensemble for mult...
Preventive and therapeutic strategies via health care delivery system to minimize sight-threatening diabetic retinopathy: a narrative review.
Current diabetes reports
Jun 10, 2025
PURPOSE OF REVIEW: To highlight various preventive and therapeutic strategies via health care delivery system to minimize sight-threatening diabetic retinopathy.
Evaluating anti-VEGF responses in diabetic macular edema: A systematic review with AI-powered treatment insights.
Indian journal of ophthalmology
May 28, 2025
Recent advances in deep learning and machine learning have greatly increased the capabilities of extracting features for evaluating the response to anti VEGF treatment in patients with Diabetic Macular Edema (DME). In this review, we explore how thes...
Non-proliferative diabetic retinopathy detection using Rosmarus Quagga optimized explainable generative meta learning based deep convolutional neural network model.
International ophthalmology
May 8, 2025
PURPOSE: Non-Proliferative Diabetic Retinopathy (NPDR) is a complication of diabetes disease where there is damage of the blood vessels in retina but with no signs of formation of new vessels. It is present in the earlier stages and therefore the con...
Deep learning segmentation of periarterial and perivenous capillary-free zones in optical coherence tomography angiography.
Journal of biomedical optics
May 8, 2025
SIGNIFICANCE: Automated segmentation of periarterial and perivenous capillary-free zones (CFZs) in optical coherence tomography angiography (OCTA) can significantly improve early detection and monitoring of diabetic retinopathy (DR), a leading cause ...
A Lesion-Fusion Neural Network for Multi-View Diabetic Retinopathy Grading.
IEEE journal of biomedical and health informatics
May 6, 2025
As the most common complication of diabetes, diabetic retinopathy (DR) is one of the main causes of irreversible blindness. Automatic DR grading plays a crucial role in early diagnosis and intervention, reducing the risk of vision loss in people with...
Latent space autoencoder generative adversarial model for retinal image synthesis and vessel segmentation.
BMC medical imaging
May 5, 2025
Diabetes is a widespread condition that can lead to serious vision problems over time. Timely identification and treatment of diabetic retinopathy (DR) depend on accurately segmenting retinal vessels, which can be achieved through the invasive techni...
A hybrid deep learning framework for early detection of diabetic retinopathy using retinal fundus images.
Scientific reports
Apr 30, 2025
Recent advancements in deep learning have significantly impacted medical image processing domain, enabling sophisticated and accurate diagnostic tools. This paper presents a novel hybrid deep learning framework that combines convolutional neural netw...
SEM model analysis of diabetic patients' acceptance of artificial intelligence for diabetic retinopathy.
BMC medical informatics and decision making
Apr 24, 2025
AIMS: This study aimed to investigate diabetic patients' acceptance of artificial intelligence (AI) devices for diabetic retinopathy screening and the related influencing factors.
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