A Discussion on the Detection and Evaluation of Diabetic Retinopathy
Keywords:
Artificial intelligence; diabetic retinopathy; domain adaptation; explainable AI; fundus; OCT.Abstract
Abstract:
Diabetic retinopathy is a leading cause of blindness in the United States. The CDC projects that the rate of DR will increase thrice between the years 2005 and 2050. A paper that provides an overview of current developments in diabetes research as well as their potential implications for therapy. Both the current course of events and potential future developments are considered. Diabetic retinopathy causes the greatest blindness worldwide. Long-term untreated diabetes produces blood glucose swings. It has become a major issue that must be addressed immediately to avoid eyesight loss in working-age people. As quickly as possible. Artificial intelligence-based diagnostic methods have been used to assess diabetic retinopathy severity and establish an initial diagnosis. Early discovery makes treatment simpler, thus eye problems may frequently be prevented. Blood vessels, microaneurysms, exudates, macula, optic discs, and hemorrhages are used to detect diabetic retinopathy in this detailed study. Most clinical research uses fundus cameras to image the retina. Fundus photos are used. This paper discusses diabetes, its incidence, consequences, and artificial intelligence methods for early diabetic retinopathy detection and categorization. Diabetes is also discussed. Machine learning and deep learning are also examined in the study. Transfer learning via generative adversarial networks, domain adaptability, multitask learning, and explainable artificial intelligence in diabetic retinopathy are all being studied. After discussing ophthalmology’s potential issues, a list of datasets, screening methods, performance measurements, and biomarkers in diabetic retinopathy is presented, followed by a conclusion on the field’s future potential. The author claims no other literature has examined contemporary state-of-the-art procedures using the PRISMA technique and artificial intelligence. Author claims.
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