Diabetic retinopathy in the pediatric population: Pathophysiology, screening, current and future treatments

Invernizzi, Alessandro; Chhablani, Jay; Viola, Francesco; Gabrielle, Pierre Henry; Zarranz‐Ventura, Javier; Staurenghi, Giovanni

doi:10.1016/j.phrs.2023.106670

Cited by 6 publications

(1 citation statement)

References 101 publications

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“…As one of the most serious microvascular complications of diabetes, DR has become the main cause of blindness [2][3] . DR is associated with various factors such as the length of the course of diabetes and the control level of blood glucose [4] . Research has shown that in patients who have had a course of diabetes for more than 10y, regardless of age, the fundus has a different course of pathological changes [5] .…”

Section: Introductionmentioning

confidence: 99%

Research progress in artificial intelligence assisted diabetic retinopathy diagnosis

Liu,

Fei,

Chen

et al. 2023

Int J Ophthalmol

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Diabetic retinopathy (DR) is one of the most common retinal vascular diseases and one of the main causes of blindness worldwide. Early detection and treatment can effectively delay vision decline and even blindness in patients with DR. In recent years, artificial intelligence (AI) models constructed by machine learning and deep learning (DL) algorithms have been widely used in ophthalmology research, especially in diagnosing and treating ophthalmic diseases, particularly DR. Regarding DR, AI has mainly been used in its diagnosis, grading, and lesion recognition and segmentation, and good research and application results have been achieved. This study summarizes the research progress in AI models based on machine learning and DL algorithms for DR diagnosis and discusses some limitations and challenges in AI research.

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Section: Introductionmentioning

confidence: 99%