AIMC Topic: Diabetic Retinopathy

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Classification of diabetes maculopathy images using data-adaptive neuro-fuzzy inference classifier.

Medical & biological engineering & computing
Prolonged diabetes retinopathy leads to diabetes maculopathy, which causes gradual and irreversible loss of vision. It is important for physicians to have a decision system that detects the early symptoms of the disease. This can be achieved by build...

Retinal vessel extraction using Lattice Neural Networks with Dendritic Processing.

Computers in biology and medicine
Retinal images can be used to detect and follow up several important chronic diseases. The classification of retinal images requires an experienced ophthalmologist. This has been a bottleneck to implement routine screenings performed by general physi...

Computer-aided diagnosis from weak supervision: a benchmarking study.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Supervised machine learning is a powerful tool frequently used in computer-aided diagnosis (CAD) applications. The bottleneck of this technique is its demand for fine grained expert annotations, which are tedious for medical image analysis applicatio...

[Adaptive lesion-aware fusion network for joint grading of multiple fundus diseases].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Diabetic retinopathy (DR) and its complication, diabetic macular edema (DME), are major causes of visual impairment and even blindness. The occurrence of DR and DME is pathologically interconnected, and their clinical diagnoses are closely related. J...

Effectiveness of artificial intelligence-based diabetic retinopathy screening in primary care and endocrinology settings in Australia: a pragmatic trial.

The British journal of ophthalmology
PURPOSE: To investigate the diagnostic accuracy, feasibility and end-user experiences of an artificial intelligence (AI)-based, automated diabetic retinopathy (DR) screening model in real-world, Australian primary care and endocrinology clinics.

Diabetic Retinopathy Screening Approaches in Developing Countries: A Systematic Review and Meta-Analysis.

Turkish journal of ophthalmology
OBJECTIVES: Diabetic retinopathy (DR) is one of the primary causes of vision loss among people living with diabetes and is expected to rise globally in the coming years. Effective screening strategies are essential, particularly in developing countri...

Diabetic retinopathy detection from fundus images: A wide survey from grading to segmentation of lesions.

Computers in biology and medicine
Diabetes is one of the most common diseases worldwide and requires accurate diagnosis. Patients with diabetes are often affected by diabetic retinopathy (DR), which can lead to low vision, vision loss, or blindness. Therefore, a robust computer-aided...

Equitable Deep Learning for Diabetic Retinopathy Detection Using Multidimensional Retinal Imaging With Fair Adaptive Scaling.

Translational vision science & technology
PURPOSE: To investigate the fairness of existing deep models for diabetic retinopathy (DR) detection and introduce an equitable model to reduce group performance disparities.

Implementing an artificial intelligence system into a diabetic eye screening programme in Tanzania.

Transactions of the Royal Society of Tropical Medicine and Hygiene
Tanzania has the highest age-adjusted prevalence of diabetes in sub-Saharan Africa. Diabetic retinopathy, a common complication, is a significant cause of vision loss; but with effective screening and treatment this often can be prevented. However, w...

Optimised Hybrid Attention-Based Capsule Network Integrated Three-Pathway Network for Chronic Disease Detection in Retinal Images.

Journal of evaluation in clinical practice
BACKGROUND: Over the past 20 years, researchers have concentrated on generating retinal images as a means of detecting and classifying chronic diseases. Early diagnosis and treatment are essential to avoid chronic diseases. Manually grading retinal i...