Ningbo Eye Hospital, Wenzhou Medical University, Ningbo 315000, China; School of Ophthalmology and Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China.
School of Ophthalmology and Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China.
Cell Rep Med. 2023 Jul 18;4(7):101095. doi: 10.1016/j.xcrm.2023.101095. Epub 2023 Jun 28.
Artificial intelligence (AI) has great potential to transform healthcare by enhancing the workflow and productivity of clinicians, enabling existing staff to serve more patients, improving patient outcomes, and reducing health disparities. In the field of ophthalmology, AI systems have shown performance comparable with or even better than experienced ophthalmologists in tasks such as diabetic retinopathy detection and grading. However, despite these quite good results, very few AI systems have been deployed in real-world clinical settings, challenging the true value of these systems. This review provides an overview of the current main AI applications in ophthalmology, describes the challenges that need to be overcome prior to clinical implementation of the AI systems, and discusses the strategies that may pave the way to the clinical translation of these systems.
人工智能（AI）具有通过提高临床医生的工作流程和生产力，使现有员工能够为更多患者提供服务，改善患者预后并减少健康差距来改变医疗保健的巨大潜力。在眼科领域，人工智能系统在糖尿病视网膜病变检测和分级等任务中的表现可与经验丰富的眼科医生相媲美，甚至更好。然而，尽管取得了这些相当不错的结果，但在实际临床环境中部署的人工智能系统却很少，这对这些系统的真正价值提出了挑战。本综述概述了当前眼科领域的主要人工智能应用，描述了在将人工智能系统临床实施之前需要克服的挑战，并讨论了可能为这些系统的临床转化铺平道路的策略。
