人工智能在糖尿病视网膜病变治疗中的应用综述:叙述性回顾

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引用次数: 1

摘要

背景:人工智能(AI),通常被称为机器智能,是一个让机器人像人一样思考的科学领域。导致视力损害和失明的最常见疾病,如年龄相关性黄斑变性(ARMD)、白内障、青光眼和糖尿病性视网膜病变(DR),最近已经成为基于深度学习的人工智能筛查和预测模型的研究对象。目的:探讨人工智能的核心思想及其在DR中的应用,评估眼科学目前面临的问题和未来。方法:本综述纳入Pubmed/MEDLINE、Google Scholar、Web of Science、Scopus、Cochrane Library等常用数据库中以“Machine Learning”、“Artificial Intelligence”、“Deep Learning”为关键词并结合“diabetic retinopathy”的英文研究。本次审查的结束日期是2022年4月。新颖性:本文阐述了人工智能的核心概念及其在糖尿病视网膜病变中的应用。目前的眼科问题和未来的机会,提供未被发现的知识,在这一领域也进行了分析。它将提高社会对使用人工智能的认识,并揭示在眼部疾病分析方面的新能力,以介绍人工智能在治疗应用方面的基本思想。结论:医疗专业人员可以使用人工智能技术做出快速准确的决策,以便分析大量数据,如生理成像和临床表现。人们相信,随着时间的推移,人工智能系统将在预测DR的发病和病程方面变得更加精确和成功。
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An overview of artificial intelligence use in diabetic retinopathy treatment: a narrative review
Background: Artificial intelligence (AI), usually called machine intelligence, is a scientific field that allows robots thinking like people. The most common diseases that cause visual impairment and blindness, such as age-related macular degeneration (ARMD), cataract, glaucoma, and diabetic retinopathy (DR), have recently been subject to deep learning-based on AI screening and prediction models. Aim: to discuss the core ideas of AI and its apply to DR, as well as to evaluate the currently faced issues and the future of ophthalmology. Methods: In this review, English studies from common databases such as Pubmed/MEDLINE, Google Scholar, Web of Science, Scopus, and the Cochrane Library with the keywords "Machine Learning," "Artificial Intelligence," "Deep Learning," combined with keywords, involving "diabetic retinopathy" were involved. The end date for this review is April 2022. Scientific novelty: This paper illustrates the core AI concepts and their application in diabetic retinopathy. The current ophthalmology issues and future opportunities, offering undiscovered knowledge in this field are also analysed. It will raise community knowledge of employing AI and reveal new capabilities in the analysis of ocular disorders to present the fundamental idea of AI regarding its therapeutic applications. Conclusion: Medical professionals can make quick and precise decisions using AI technologies in orded to analyse massive volumes of data, such as physiological imaging and clinical presentations. It is believed that over time, AI systems will become more precise and successful at predicting the onset and course of DR.
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