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Artificial neural networks allow the use of simultaneous measurements of Alzheimer Disease markers for early detection of the disease

机译:人工神经网络允许同时测量阿尔茨海默氏病标志物以早期发现疾病

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摘要

BackgroundPrevious studies have shown that in platelets of mild Alzheimer Disease (AD) patients there are alterations of specific APP forms, paralleled by alteration in expression level of both ADAM 10 and BACE when compared to control subjects. Due to the poor linear relation among each key-element of beta-amyloid cascade and the target diagnosis, the use of systems able to afford non linear tasks, like artificial neural networks (ANNs), should allow a better discriminating capacity in comparison with classical statistics.
机译:背景先前的研究表明,与对照组相比,轻度阿尔茨海默病(AD)患者的血小板存在特定APP形式的改变,同时ADAM 10和BACE的表达水平也发生改变。由于β-淀粉样蛋白级联的每个关键元素与目标诊断之间的线性关系较差,因此与经典算法相比,使用能够提供非线性任务的系统(如人工神经网络(ANN))应该可以更好地区分统计。

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