Mai Julia, Schmidt-Erfurth Ursula
Universitätsklinik für Augenheilkunde und Optometrie, Medizinische Universität Wien, Österreich.
Klin Monbl Augenheilkd. 2024 Sep;241(9):1023-1031. doi: 10.1055/a-2378-6138. Epub 2024 Sep 16.
Artificial intelligence (AI) has already found its way into ophthalmology, with the first approved algorithms that can be used in clinical routine. Retinal diseases in particular are proving to be an important area of application for AI, as they are the main cause of blindness and the number of patients suffering from retinal diseases is constantly increasing. At the same time, regular imaging using high-resolution modalities in a standardised and reproducible manner generates immense amounts of data that can hardly be processed by human experts. In addition, ophthalmology is constantly experiencing new developments and breakthroughs that require a re-evaluation of patient management in routine clinical practice. AI is able to analyse these volumes of data efficiently and objectively and also provide new insights into disease progression and therapeutic mechanisms by identifying relevant biomarkers. AI can make a significant contribution to screening, classification and prognosis of various retinal diseases and can ultimately be a clinical decision support system, that significantly reduces the burden on both everyday clinical practice and the healthcare system, by making more efficient use of costly and time-consuming resources.
人工智能(AI)已经进入眼科领域,出现了首批可用于临床常规的获批算法。事实证明,视网膜疾病尤其成为AI的一个重要应用领域,因为它们是失明的主要原因,且患有视网膜疾病的患者数量在不断增加。与此同时,以标准化和可重复的方式使用高分辨率模式进行定期成像会产生海量数据,人类专家几乎难以处理这些数据。此外,眼科领域不断有新的发展和突破,这就需要在常规临床实践中重新评估患者管理。AI能够高效、客观地分析这些大量数据,还能通过识别相关生物标志物为疾病进展和治疗机制提供新见解。AI可为各种视网膜疾病的筛查、分类和预后做出重大贡献,并最终成为一个临床决策支持系统,通过更有效地利用昂贵且耗时的资源,显著减轻日常临床实践和医疗系统的负担。