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SYSTEM AND METHOD FOR ANALYZING AD OR MCI OR CN DISEASE DEVELOPMENT TREND BY MEANS OF MULTI-MODAL MODELING

机译:通过多模态建模分析AD或MCI或CN疾病发展趋势的系统和方法

摘要

The present invention belongs to the field of computer application, and particularly relates to a system and method for analyzing an AD or MCI or CN disease development trend by means of multi-modal modeling. The system comprises: a model A composed of clinical medicine data and an apolipoprotein E data input module and a non-linear classifier; a model B composed of a genomic data input module and a non-linear classifier; a model C composed of MRI data, a convolutional neural network and a recurrent neural network; an ADNI data set; and a model D composed of prediction value receiving modules of the model A, the model B and the model C, and a logistic regression model, wherein the ADNI data set provides the clinical medicine data, apolipoprotein E data, genomic data and the MRI data. On the basis of a traditional method and a deep learning method, by means of the present invention, the two methods are combined by means of multi-modal modeling, and more a priori information and external features are added, such that the generalization ability of a model can be enhanced to a certain extent.
机译:本发明属于计算机应用领域,具体涉及一种通过多模态建模分析AD或MCI或CN疾病发展趋势的系统和方法。该系统包括:由临床医学数据、载脂蛋白E数据输入模块和非线性分类器组成的模型a;模型B由基因组数据输入模块和非线性分类器组成;模型C由MRI数据、卷积神经网络和递归神经网络组成;ADNI数据集;模型D由模型a、模型B和模型C的预测值接收模块和逻辑回归模型组成,其中ADNI数据集提供临床医学数据、载脂蛋白E数据、基因组数据和MRI数据。在传统方法和深度学习方法的基础上,通过本发明,通过多模态建模将这两种方法结合起来,并添加更多的先验信息和外部特征,从而在一定程度上提高模型的泛化能力。

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