Department of Biomedical, Surgical and Dental Sciences, University of Milan.
Eye Clinic, IRCCS MultiMedica.
Curr Opin Ophthalmol. 2024 Nov 1;35(6):472-479. doi: 10.1097/ICU.0000000000001084. Epub 2024 Sep 9.
Given 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.
Most 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.
This 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.
目的综述:鉴于糖尿病视网膜病变的全球负担不断增加以及人工智能的快速发展,本综述旨在总结人工智能技术在糖尿病视网膜病变检测和管理中的现状,评估其在真实环境中改善护理和视觉结果的潜力。
最新发现:最近的大多数研究都集中在人工智能在糖尿病视网膜病变筛查领域的整合上,重点关注此类人工智能模型在实际中的效果和临床应用。此外,人工智能还有望通过“眼科学”预测糖尿病视网膜病变的进展、增强个性化治疗策略,并从眼部图像中识别系统性疾病生物标志物,朝着更精确、更高效、更便捷的护理方向发展。基础模型架构和生成式人工智能的出现,更清晰地反映了临床护理过程,可能会推动糖尿病视网膜病变护理、研究和医学教育的快速发展。
总结:本综述探讨了新兴的人工智能技术,评估其改善患者结局和优化医疗保健提供和医学研究中个性化管理的潜力。虽然人工智能有望在糖尿病视网膜病变的护理中发挥越来越重要的作用,但仍需要开展进一步的研究和临床试验,以解决实施问题,并关注人工智能在糖尿病视网膜病变中的成功实际应用的长期患者结局。