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视网膜成像和阿尔茨海默病:由人工智能驱动的未来

Hamidreza Ashayeri¹, Ali Jafarizadeh², Milad Yousefi³

¹Neuroscience Research Center (NSRC), Tabriz University of Medical Sciences, Tabriz, Iran.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie

|February 15, 2024

概括

人工智能 (AI) 分析视网膜图像以检测阿尔茨海默病 (AD) 变化,帮助早期预测和诊断. 这项技术在识别有风险的个体和评估疾病预后方面表现有前途.

科学领域:

眼科医生眼科眼科
神经学神经学
人工智能的人工智能

背景情况:

阿尔茨海默病 (AD) 是一种神经退行性疾病,影响大脑组织.
视网膜和大脑之间的共同胚胎起源导致阿兹海默病患者的视力缺陷.
视网膜变化,包括厚度和血管密度的变化,可以在临床AD症状之前.

研究的目的:

审查人工智能 (AI) 在分析视网膜图像中对阿尔茨海默病 (AD) 预测,诊断和预后的应用.
讨论AI在检测与AD相关的微妙视网膜变化的潜力.
探索使用视网膜成像检测ADAI算法和数据集的发展.

主要方法:

在阿尔茨海默病中对人工智能和视网膜成像现有研究的审查.
对在视网膜图像上训练的AI算法进行分析,以识别AD的标志.
利用机器视觉来检测视网膜厚度和血管密度的变化.

主要成果:

人工智能在将视网膜图像分类为AD患者和健康人群中表现出高准确度,灵敏度和特异性.
人工智能可以根据视网膜图像特征识别具有阿尔茨海默氏病家族史的个体.
视网膜OCTA细分 (ROSE) 数据集的开发有助于人工智能研究AD.

结论:

人工智能对使用视网膜成像进行阿尔茨海默病的预测,诊断和预后具有重大潜力.
人工智能驱动的视网膜变化的分析提供了一个非侵入性的方法来检测AD.
需要进一步的队列研究来验证AI在监测有风险的个体和评估AD预后方面的作用.

关键词:

阿尔茨海默氏症是阿尔茨海默氏症的一种疾病.人工智能的人工智能是人工智能.深度学习是一种深度学习.机器学习机器学习视网膜 (retina) 是一个视网膜.视网膜图像视网膜图像审查审查审查审查

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