Artificial intelligence for retinal diseases

IF 3.7 3区 医学 Q1 OPHTHALMOLOGY Asia-Pacific Journal of Ophthalmology Pub Date : 2024-07-01 DOI:10.1016/j.apjo.2024.100096
Jennifer I. Lim , Aleksandra V. Rachitskaya , Joelle A. Hallak , Sina Gholami , Minhaj N. Alam
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Abstract

Purpose

To discuss the worldwide applications and potential impact of artificial intelligence (AI) for the diagnosis, management and analysis of treatment outcomes of common retinal diseases.

Methods

We performed an online literature review, using PubMed Central (PMC), of AI applications to evaluate and manage retinal diseases. Search terms included AI for screening, diagnosis, monitoring, management, and treatment outcomes for age-related macular degeneration (AMD), diabetic retinopathy (DR), retinal surgery, retinal vascular disease, retinopathy of prematurity (ROP) and sickle cell retinopathy (SCR). Additional search terms included AI and color fundus photographs, optical coherence tomography (OCT), and OCT angiography (OCTA). We included original research articles and review articles.

Results

Research studies have investigated and shown the utility of AI for screening for diseases such as DR, AMD, ROP, and SCR. Research studies using validated and labeled datasets confirmed AI algorithms could predict disease progression and response to treatment. Studies showed AI facilitated rapid and quantitative interpretation of retinal biomarkers seen on OCT and OCTA imaging. Research articles suggest AI may be useful for planning and performing robotic surgery. Studies suggest AI holds the potential to help lessen the impact of socioeconomic disparities on the outcomes of retinal diseases.

Conclusions

AI applications for retinal diseases can assist the clinician, not only by disease screening and monitoring for disease recurrence but also in quantitative analysis of treatment outcomes and prediction of treatment response. The public health impact on the prevention of blindness from DR, AMD, and other retinal vascular diseases remains to be determined.

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人工智能治疗视网膜疾病。
目的:讨论人工智能(AI)在常见视网膜疾病的诊断、管理和治疗效果分析方面的全球应用及其潜在影响:我们利用 PubMed Central (PMC),对人工智能在评估和管理视网膜疾病方面的应用进行了在线文献综述。检索词包括人工智能对老年性黄斑变性(AMD)、糖尿病视网膜病变(DR)、视网膜手术、视网膜血管疾病、早产儿视网膜病变(ROP)和镰状细胞视网膜病变(SCR)的筛查、诊断、监测、管理和治疗效果。其他检索词包括 AI 和彩色眼底照片、光学相干断层扫描 (OCT) 和 OCT 血管造影术 (OCTA)。我们收录了原创研究文章和综述文章:研究表明,人工智能在筛查 DR、AMD、ROP 和 SCR 等疾病方面具有实用性。使用经过验证和标记的数据集进行的研究证实,人工智能算法可以预测疾病的进展和对治疗的反应。研究表明,人工智能有助于快速、定量地解读 OCT 和 OCTA 成像上的视网膜生物标记物。研究文章表明,人工智能可能有助于规划和实施机器人手术。研究表明,人工智能有可能帮助减少社会经济差异对视网膜疾病治疗效果的影响:人工智能在视网膜疾病方面的应用可以帮助临床医生,不仅可以进行疾病筛查和监测疾病复发,还可以对治疗结果进行定量分析并预测治疗反应。人工智能对预防 DR、AMD 和其他视网膜血管疾病致盲的公共卫生影响仍有待确定。
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来源期刊
CiteScore
8.10
自引率
18.20%
发文量
197
审稿时长
6 weeks
期刊介绍: The Asia-Pacific Journal of Ophthalmology, a bimonthly, peer-reviewed online scientific publication, is an official publication of the Asia-Pacific Academy of Ophthalmology (APAO), a supranational organization which is committed to research, training, learning, publication and knowledge and skill transfers in ophthalmology and visual sciences. The Asia-Pacific Journal of Ophthalmology welcomes review articles on currently hot topics, original, previously unpublished manuscripts describing clinical investigations, clinical observations and clinically relevant laboratory investigations, as well as .perspectives containing personal viewpoints on topics with broad interests. Editorials are published by invitation only. Case reports are generally not considered. The Asia-Pacific Journal of Ophthalmology covers 16 subspecialties and is freely circulated among individual members of the APAO’s member societies, which amounts to a potential readership of over 50,000.
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