Smartphone Eye Examination: Artificial Intelligence and Telemedicine

远程医疗 检眼镜 软件可移植性 计算机科学 梅德林 人口 人工智能 医学 科克伦图书馆 验光服务 医学物理学 医疗保健 荟萃分析 眼科 病理 政治学 法学 经济 程序设计语言 经济增长 环境卫生 视网膜
作者
Manuel Vilela,Alessandro Arrigo,Maurízio Battaglia Parodi,Carolina da Silva Mengue
出处
期刊:Telemedicine Journal and E-health [Mary Ann Liebert, Inc.]
卷期号:30 (2): 341-353 被引量:7
标识
DOI:10.1089/tmj.2023.0041
摘要

Background: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. Methods: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. Results: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. Conclusions: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.
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