
AI analyses retinal images captured during screening to detect early signs of diabetic retinopathy and support large-scale eye disease screening programs.
Diabetic retinopathy is a major cause of preventable blindness among people with diabetes. Early detection through regular retinal screening can significantly reduce the risk of vision loss. However, large-scale screening programs often face challenges due to limited availability of ophthalmologists and specialized diagnostic equipment.
AI-enabled retinal screening systems analyse retinal photographs captured at primary healthcare facilities. Deep learning models trained on large datasets of retinal images identify signs of diabetic retinopathy such as microaneurysms, hemorrhages, and retinal swelling.
For additional context and detailed documentation of this use case, please refer to pages 258-259 in the attached Casebook.
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