A Systemic Review: an Early Detection of Diabetic Retinopathy using Artificial Intelligence

The global prevalence of diabetes is rapidly increasing, with over 463 million adults currently affected. This rise has led to a significant increase in diabetic-related eye conditions, particularly diabetic retinopathy (DR), which is now a leading cause of blindness among adults. DR results from damage to the blood vessels in the retina and often progresses without noticeable symptoms until vision is affected. Due to the growing diabetic population, effective screening for DR has become a major challenge, with millions of retinal images requiring analysis each year. Early detection is crucial, as most vision loss from DR is preventable. Traditional diagnostic methods like ophthalmoscopy are still in use, but emerging technologies such as artificial intelligence (AI), deep learning, and big data are proving to be valuable tools in enhancing early diagnosis and treatment planning.