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首页> 外文期刊>International journal of reasoning-based intelligent systems >Classification and prediction of Alzheimer's disease using multi-layer perceptron
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Classification and prediction of Alzheimer's disease using multi-layer perceptron

机译:使用多层扰动阿尔茨海默病的分类与预测

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摘要

With the changing lifestyle, there is a tremendous increase in the cases of Alzheimer's disease. People are not able to pacify their urge of accurate diagnosis till date. The main reason for this increment is the changing lifestyle of today's generation because of which they are not able to meet their daily body requirements schedule which can keep them fit both physically and mentally. From childhood to adolescent to middle age, this carelessness does not show any signs of its glimpses but when a person hits the old age, it becomes prominent. In this paper, we have classified the patients suffering from Alzheimer's disease using the National Alzheimer's Coordinating Centre's (NACC's) database with the help of random forest (RF), support vector machine (SVM), K-nearest neighbour (KNN), linear discriminate analysis (LDA) and neural networks (NN). We also used the multi-layer perceptron (MLP) for classification of MRI data and the outcome signified that it proved to be the most competent approach with 94% accuracy.
机译:随着生活方式的变化,在阿尔茨海默病的病例中存在巨大增加。人们无法安抚他们的准确诊断促使到目前为止。这种增量的主要原因是当今世代的改变生活方式不断变化,因为它们无法满足他们的日常的身体要求计划,这可以让它们保持身体和精神上。从童年到青少年到中年,这种粗心不良并不显示出其瞥见的任何迹象,但当一个人击中年龄时,它变得突出。在本文中,我们将患有Alzheimer的疾病的患者分类为使用国家阿尔茨海默的协调中心(NACC)数据库,随机森林(RF),支持向量机(SVM),K最近邻(KNN),线性鉴别分析(LDA)和神经网络(NN)。我们还使用了MARI数据分类的多层Perceptron(MLP),结果表示,它被证明是最有能力的方法,准确性为94%。

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