Diabetic Retinopathy
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Collaborative Care for Diabetic Retinopathy: Integrating Artificial Intelligence and Clinical Pharmacy Services - A Comprehensive Review
Abstract: Background: Diabetic retinopathy (DR) remains the leading cause of blindness among working-age adults globally, affecting approximately 103 million people worldwide. The integration of artificial intelligence (AI) technologies with clinical pharmacy services presents unprecedented opportunities to enhance screening, diagnosis, and management of DR through collaborative care models. Objective: This comprehensive review examines the current landscape of collaborative care approaches for diabetic retinopathy management, focusing on the integration of AI-powered diagnostic tools …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 118–128 Read article
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A Comprehensive Review of CNN-Based Framework for Multi-Sign Detection of Diabetic Retinopathy in Fundus Images Using Public Datasets
Abstract: Diabetic retinopathy (DR) is one of the main causes of vision impairment. Blindness prevention and effective treatment depend on early detection. A thorough deep learning-based framework for the automatic segmentation and simultaneous detection of exudates, hemorrhages, and microaneurysms – three important DR indicators – from retinal fundus images is presented in this work. These three pathological signs’ corresponding annotated image patches, along with background (no-sign) areas, were used to train …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 14–23 Read article
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A summary continuation analysis evaluating the prevalence and predictors of diabetic retinopathy in newly diagnosed type 2 diabetic patients.
Abstract: Context: Diabetic retinopathy (DR), the leading cause of acquired blindness in adults, affects approximately 93 million people globally. It is a serious complication of type 2 diabetes, resulting from prolonged damage to the blood vessels in the retina. Although largely preventable and treatable, DR continues to be the main cause of vision loss among working-age adults and significantly impacts quality of life. While most studies on DR in Nepal have …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 21–30 Read article
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The Analysis of Deep Learning-Based Methods for Identifying Diabetic Retinopathy
Abstract: Diabetic retinopathy (DR) is a degenerative eye condition resulting from diabetes mellitus, where high blood glucose levels lead to lesions on the retina. This condition is considered the leading cause of blindness among working-age diabetic patients, particularly in developing countries. As the disease is irreversible, the treatment aims to preserve the patient’s current vision. Early detection is crucial for effective management of DR to maintain vision. One of the main …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 · pp. 15–31 Read article
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Recent Trends in Ocular Drug Delivery: Challenges and Approaches
Abstract: Drug topically regulation can be accessed most easily in the eye. When given topically as eye drops, medication ocular bioavailability is quite low. Drug entry into specific ocular locations is complicated by the complex anatomy and physiology of the human eye. Research has long been interested in the topical administration of successful treatments. To provide a suitable ocular penetration and extend the duration of drug residence is their challenging task. …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 11, Issue 3, 2024 · pp. 22–38 Read article
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Detection and Classification of Diabetic Retinopathy Using Deep Learning Techniques
Abstract: This project delves into the evaluation of three prominent deep learning architectures Basic CNN, ResNet, and DenseNet for their efficacy in detecting diabetic retinopathy from retinal images. Utilizing a diverse dataset, the study employs standard deep learning frameworks to train and validate each model. The focus extends to exploring the potential benefits of transfer learning on a limited dataset. Evaluation metrics like specificity, sensitivity, and accuracy are employed for a …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 64–69 Read article
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Exploring Diabetic Retinopathy from an Ayurvedic Lens: Insights Leveraging Bioinformatics
Abstract: Diabetic retinopathy is one among the target diseases for VISION 2025. The huge cost required for treatment, economic loss due to absenteeism from work etc... has made it as a great public challenge. Therefore it is in need of the hour to address the issues of diabetes mellitus with its complication Diabetic Retinopathy with all seriousness and it is quite essential to search for a affordable medical care for the …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 2, 2024 · pp. 45–51 Read article