What is it about?
Diabetic retinopathy (DR), a major microvascular complication of diabetes, has a significant impact on the world's health systems. Globally, the number of people with DR will grow from 126.6 million in 2010 to 191.0 million by 2030. Diabetic retinopathy (DR) is often neglected in low-income countries due to limited access to trained eye-care professionals. Innovative and comprehensive approaches are needed to reduce the risk of vision loss by prompt diagnosis.
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Why is it important?
Although deep learning models yield effective results in experimental, laboratory-level conditions, a loss of performance is incurred when they are evaluated in a clinical environment. In order to accelerate the accuracy, they must be developed in consultation with expert ophthalmologists and validated in operational clinical settings. Implementing DR detection in telemedicine's is a major challenge due to interpretation.
Perspectives
Our study represents a significant step towards the development of more effective and accessible screening methods for DR and DME, with the ultimate goal of preventing vision loss and improving the quality of life for patients with diabetes.
Balamurugan V
Sona College of Technology
Read the Original
This page is a summary of: Advanced grading and individualized guidance for diabetic retinopathy and Macular Edema care, January 2025, American Institute of Physics,
DOI: 10.1063/5.0263176.
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