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验证和完善阿尔茨海默病进展的早期状态:深度特征比较的可能性

Mianxin Liu^1,2, Liang Cui³, Zixiao Zhao⁴

¹School of Biomedical Engineering, State Key Laboratory of Advanced Medical Materials and Devices, Shanghai Tech University, Shanghai 201210, China.

Cerebral cortex (New York, N.Y. : 1991)

|October 13, 2023

概括

深度学习揭示了主观认知衰退,缓解认知障碍和阿尔茨海默病之间的相似之处. 这表明了潜在的进展途径,有助于定义阿尔茨海默氏症早期阶段.

科学领域:

神经科学是一个神经科学.
人工智能的人工智能
医学诊断医学诊断医学诊断

背景情况:

定义早期阿尔茨海默病 (AD) 阶段是复杂的.
理论表明,在AD连续体中存在共同的特征.
完善早期诊断标准对于及时干预至关重要.

研究的目的:

通过深度学习功能来验证和完善早期阿尔茨海默病的状态.
探索不同认知状态之间的特征相似性.
在早期认知衰退中识别信息子群.

主要方法:

在大脑功能网络上训练深度学习模型.
它被分为记忆力和非记忆力轻度认知障碍 (MCI).
在健康对照 (HC) 和MCI之间分类.
将模型应用于阿尔茨海默病 (AD) 和主观认知衰退 (SCD) 组.

主要成果:

分类器在AD,MCI和SCD之间发现了显著的重叠.
71.8%的AD病例被归类为无记忆性MCI.
73.5%的SCD被归类为MCI,其中88.8%的人被归类为大赦MCI.
带有无记忆性MCI类特征的子群体显示出更大的AD病理.

结论:

强有力的证据表明,SCD,记忆遗忘性MCI和AD之间存在总体相似性和进展关系.
深度特征比较是完善早期AD状态的一个有希望的框架.
在早期认知衰退中,确定了具有不同病理特征的独特亚群.

关键词:

阿尔茨海默病的连续性是阿尔茨海默病的连续性功能连接性的功能连接性图表卷积网络卷积网络轻度的认知障碍轻度的认知障碍主观认知衰退主观认知衰退

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