Irodi Anushka, Zhu Zhuoting, Grzybowski Andrzej, Wu Yilan, Cheung Carol Y, Li Huating, Tan Gavin, Wong Tien Yin
School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom.
Centre for Eye Research Australia, Ophthalmology, University of Melbourne, Melbourne, Australia.
Eye (Lond). 2025 Apr;39(6):1040-1046. doi: 10.1038/s41433-025-03633-4. Epub 2025 Feb 5.
Diabetic retinopathy (DR) is a leading cause of preventable blindness and has emerged as a global health challenge, necessitating the development of robust management strategies. As DR prevalence continues to rise, advancements in screening methods have become increasingly critical for timely detection and intervention. This review examines three key advancements in DR screening: a shift from specialist to generalist approach, the adoption of telemedicine strategies for expanded access and enhanced efficiency, and the integration of artificial intelligence (AI). In particular, AI offers unprecedented benefits in the form of sustainability and scalability for not only DR screening but other aspects of eye health and the medical field as a whole. Though there remain barriers to address, AI holds vast potential for reshaping DR screening and significantly improving patient outcomes globally.
糖尿病视网膜病变（DR）是可预防失明的主要原因，已成为一项全球性健康挑战，因此需要制定强有力的管理策略。随着DR患病率持续上升，筛查方法的进步对于及时检测和干预变得越来越关键。本综述探讨了DR筛查的三项关键进展：从专科医生主导模式向全科医生主导模式的转变、采用远程医疗策略以扩大可及性并提高效率，以及人工智能（AI）的整合。特别是，AI不仅为DR筛查，也为整个眼部健康和医学领域的其他方面带来了前所未有的可持续性和可扩展性优势。尽管仍有障碍需要克服，但AI在重塑DR筛查并显著改善全球患者治疗效果方面具有巨大潜力。
