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Modeling of Parkinson's Disease Using Fuzzy Cognitive Maps and Non-Linear Hebbian Learning

机译:使用模糊认知图和非线性Hebbian学习对帕金森氏病建模

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摘要

Parkinson's disease is a chronic, progressive, age-related, neurodegenerative disorder that affects a large population around the world. A mathematical model for Parkinson's disease is presented using Fuzzy Cognitive Maps (FCMs). Basic theories of FCMs are reviewed and presented. Decision Support Systems (DSS) for medical problems are reviewed. Non-linear Hebbian learning techniques are considered in studying Medical problems and a generic algorithm is presented. The proposed method used the knowledge of a number of experts and simulations were performed obtaining interesting results. Comparisons of the results of the proposed method, both by making use and not making use of learning algorithms, are presented. Some interesting future research directions are mentioned.
机译:帕金森氏病是一种慢性,进行性,与年龄相关的神经退行性疾病,会影响世界各地的大量人口。使用模糊认知图(FCM)提出了帕金森氏病的数学模型。审查和介绍了FCM的基本理论。审查了医疗问题的决策支持系统(DSS)。在研究医学问题时考虑了非线性Hebbian学习技术,并提出了一种通用算法。所提出的方法利用了许多专家的知识,并进行了仿真,获得了有趣的结果。通过使用和不使用学习算法,对提出的方法的结果进行了比较。提到了一些有趣的未来研究方向。

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