Department of Ophthalmology, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil.
Department of Ophthalmology, Scientific Institute San Raffaele, Milan, Italy.
Telemed J E Health. 2024 Feb;30(2):341-353. doi: 10.1089/tmj.2023.0041. Epub 2023 Aug 16.
The current medical scenario is closely linked to recent progress in telecommunications, photodocumentation, and artificial intelligence (AI). Smartphone eye examination may represent a promising tool in the technological spectrum, with special interest for primary health care services. Obtaining fundus imaging with this technique has improved and democratized the teaching of fundoscopy, but in particular, it contributes greatly to screening diseases with high rates of blindness. Eye examination using smartphones essentially represents a cheap and safe method, thus contributing to public policies on population screening. This review aims to provide an update on the use of this resource and its future prospects, especially as a screening and ophthalmic diagnostic tool. In this review, we surveyed major published advances in retinal and anterior segment analysis using AI. We performed an electronic search on the Medical Literature Analysis and Retrieval System Online (MEDLINE), EMBASE, and Cochrane Library for published literature without a deadline. We included studies that compared the diagnostic accuracy of smartphone ophthalmoscopy for detecting prevalent diseases with an accurate or commonly employed reference standard. There are few databases with complete metadata, providing demographic data, and few databases with sufficient images involving current or new therapies. It should be taken into consideration that these are databases containing images captured using different systems and formats, with information often being excluded without essential detailing of the reasons for exclusion, which further distances them from real-life conditions. The safety, portability, low cost, and reproducibility of smartphone eye images are discussed in several studies, with encouraging results. The high level of agreement between conventional and a smartphone method shows a powerful arsenal for screening and early diagnosis of the main causes of blindness, such as cataract, glaucoma, diabetic retinopathy, and age-related macular degeneration. In addition to streamlining the medical workflow and bringing benefits for public health policies, smartphone eye examination can make safe and quality assessment available to the population.
当前的医学现状与电信、光记录和人工智能（AI）的最新进展密切相关。智能手机眼部检查可能是技术领域中很有前途的工具，特别适用于初级卫生保健服务。通过这种技术获得眼底图像，改善了眼底镜检查的教学，并使筛查高致盲率疾病的工作变得更加容易。使用智能手机进行眼部检查本质上是一种廉价且安全的方法，因此有助于制定人口筛查的公共政策。本文旨在提供关于该资源使用情况及其未来前景的最新信息，特别是作为一种筛查和眼科诊断工具。
在这篇综述中，我们调查了使用 AI 进行视网膜和前段分析的主要已发表进展。我们在 MEDLINE、EMBASE 和 Cochrane 图书馆上进行了电子检索，检索无截止日期的已发表文献。我们纳入了比较智能手机眼科检查对检测常见疾病的诊断准确性的研究，这些疾病的诊断准确性与准确或常用的参考标准相当。
只有少数数据库具有完整的元数据，提供人口统计学数据，而很少有数据库具有足够的涉及当前或新疗法的图像。应考虑到这些数据库包含使用不同系统和格式拍摄的图像，并且信息经常被排除，而没有详细说明排除的原因，这进一步使它们脱离了现实生活条件。一些研究讨论了智能手机眼部图像的安全性、便携性、低成本和可重复性，并取得了令人鼓舞的结果。
传统方法和智能手机方法之间的高度一致性表明，它是筛查和早期诊断白内障、青光眼、糖尿病视网膜病变和年龄相关性黄斑变性等主要致盲原因的有力武器。除了简化医疗工作流程并为公共卫生政策带来益处外，智能手机眼部检查还可以为公众提供安全和质量评估。
