Interdisciplinary

AI Detects Diabetic Eye Disease Earlier Than Traditional Methods

How the science connects

Artificial intelli…Machine learningDiabetic retinopathy

AI Insight

This is a correction notice published by PLOS ONE staff regarding a previously published article about using artificial intelligence and vision transformer models for early detection of diabetic retinopathy. The original article explored applying advanced machine learning techniques to identify diabetic retinopathy in its early stages through automated image analysis. No substantive findings are presented in this correction notice itself, as it serves only to address errors in the original publication.


Early detection of diabetic retinopathy is critical for preventing vision loss in diabetic patients, and AI-based screening tools could improve accessibility and efficiency of diagnostic services. However, this particular document is merely an administrative correction and does not contribute new scientific knowledge to the field.


by The PLOS One Staff

Source: Correction: Artificial intelligence for early detection of diabetic retinopathy: A vision transformer-based approach