Novel artificial intelligence for diabetic retinopathy and diabetic macular edema: what is new in 2024?

被引:2
作者
Vujosevic, Stela [1 ,2 ]
Limoli, Celeste [3 ]
Nucci, Paolo [1 ]
机构
[1] Univ Milan, Dept Biomed Surg & Dent Sci, Via San Vittore 12, I-20123 Milan, MI, Italy
[2] Univ Milan, Eye Clin, IRCCS Multimed, Milan, Italy
[3] Univ Milan, Dept Ophthalmol, Milan, Italy
关键词
artificial intelligence; deep learning; diabetic retinopathy; foundation model; retinal imaging; MODEL; AI; EYE;
D O I
10.1097/ICU.0000000000001084
中图分类号
R77 [眼科学];
学科分类号
100212 ;
摘要
Purpose of reviewGiven the increasing global burden of diabetic retinopathy and the rapid advancements in artificial intelligence, this review aims to summarize the current state of artificial intelligence technology in diabetic retinopathy detection and management, assessing its potential to improve care and visual outcomes in real-world settings.Recent findingsMost recent studies focused on the integration of artificial intelligence in the field of diabetic retinopathy screening, focusing on real-world efficacy and clinical implementation of such artificial intelligence models. Additionally, artificial intelligence holds the potential to predict diabetic retinopathy progression, enhance personalized treatment strategies, and identify systemic disease biomarkers from ocular images through 'oculomics', moving towards a more precise, efficient, and accessible care. The emergence of foundation model architectures and generative artificial intelligence, which more clearly reflect the clinical care process, may enable rapid advances in diabetic retinopathy care, research and medical education.SummaryThis review explores the emerging technology of artificial intelligence to assess the potential to improve patient outcomes and optimize personalized management in healthcare delivery and medical research. While artificial intelligence is expected to play an increasingly important role in diabetic retinopathy care, ongoing research and clinical trials are essential to address implementation issues and focus on long-term patient outcomes for successful real-world adoption of artificial intelligence in diabetic retinopathy.
引用
收藏
页码:472 / 479
页数:8
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