The potential role played by artificial adaptive systems in enhancing our understanding of Alzheimer disease: The experience gained within Italian Interdisciplinary network on Alzheimer disease

E. Grossi, M. Buscema
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引用次数: 3

Abstract

The author describes a refiguration of medical thought which originate from non linear dynamics and chaos theory. The coupling of computer science and these new theoretical bases allows the creation of “intelligent” agents (Artificial Adaptive Systems AAS) able to adapt themselves dynamically to problem of high complexity like Alzheimer Disease. ASS are able to reproduce the dynamical interactio of multiple factors simultaneously, allowing the study of complexity; they can also draw conclusions on individual basis and not as average trends. In the last years of co-operation between ITINAD, Bracco Medical Department and Semeion Research Centre different kinds of experiments have been performed with ANNs in Alzheimer Disease context. The specific application of ANN in most cases is original, and has followed two principal aims: –prediction of outcome or diagnosis in individual patients; –data mining of complex data sets. Several examples of applications will be described.
人工适应系统在增强我们对阿尔茨海默病的理解方面所发挥的潜在作用:意大利阿尔茨海默病跨学科网络所获得的经验
作者描述了一种源于非线性动力学和混沌理论的医学思想重构。计算机科学和这些新的理论基础的结合使得“智能”代理(人工适应系统)能够动态地适应像阿尔茨海默病这样高度复杂的问题。人工智能系统能够同时再现多个因素的动态相互作用,允许对复杂性进行研究;他们还可以根据个人情况得出结论,而不是根据平均趋势得出结论。在ITINAD、博莱科医学部门和Semeion研究中心过去几年的合作中,在阿尔茨海默病的背景下,用人工神经网络进行了不同类型的实验。在大多数情况下,人工神经网络的具体应用是原创的,并遵循两个主要目的:预测个体患者的预后或诊断;-复杂数据集的数据挖掘。将描述几个应用程序示例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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