Talcott Katherine E, Kim Judy E, Modi Yasha, Moshfeghi Darius M, Singh Rishi P
Center for Ophthalmic Bioinformatics, Cole Eye Institute, Cleveland Clinic Foundation, Cleveland, OH, USA.
Cleveland Clinic Lerner College of Medicine, Cleveland, OH, USA.
J Vitreoretin Dis. 2020 Mar 27;4(4):312-319. doi: 10.1177/2474126420914168. eCollection 2020 Jul-Aug.
Artificial intelligence (AI) is a growing area that relies on the heavy use of diagnostic imaging within the field of retina to offer exciting advancements in diagnostic capability to better understand and manage retinal conditions such as diabetic retinopathy, diabetic macular edema, age-related macular degeneration, and retinopathy of prematurity. However, there are discrepancies between the findings of these AI programs and their referral recommendations compared with evidence-based referral patterns, such as Preferred Practice Patterns by the American Academy of Ophthalmology. The overall focus of this task force report is to first describe the work in AI being completed in the management of retinal conditions. This report also discusses the guidelines of the Preferred Practice Pattern and how they can be used in the emerging field of AI.
人工智能（AI）是一个不断发展的领域，它在视网膜领域大量依赖诊断成像技术，为更好地理解和管理诸如糖尿病性视网膜病变、糖尿病性黄斑水肿、年龄相关性黄斑变性和早产儿视网膜病变等视网膜疾病的诊断能力带来了令人兴奋的进展。然而，与基于证据的转诊模式（如美国眼科学会的《首选实践模式》）相比，这些人工智能程序的研究结果及其转诊建议之间存在差异。本特别工作组报告的总体重点是首先描述在视网膜疾病管理中正在完成的人工智能工作。本报告还讨论了《首选实践模式》的指南以及它们如何在人工智能的新兴领域中使用。
