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Prediction of Alzheimer's Disease Based on Coordinate-Dense Attention Network

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成果类型：

会议论文

作者：

Tang Y.;Liao X.;Si W.;Ning Z.

通讯作者：

Liao, X.

作者机构：

[Ning Z.] University of South China, Hengyang, China

[Si W.; Liao X.] Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

[Tang Y.] University of South China, Hengyang, China, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

通讯机构：

[Liao, X.] S

Shenzhen Institute of Advanced Technology, China

语种：

英文

关键词：

Alzheimer's disease;Convolutional neural network;Deep learning

期刊：

Frontiers in Artificial Intelligence and Applications

ISSN：

0922-6389

年：

2021

卷：

345

页码：

63-70

会议名称：

11th International Conference on Electronics, Communications and Networks, CECNet 2021

会议时间：

18 November 2021 through 21 November 2021

主编：

Tallon-Ballesteros A.J.

出版者：

IOS Press BV

ISBN：

9781643682402

DOI：

10.3233/FAIA210390

基金类别：

This work is supported by multiple grants, including: The National Key Research and Development Program of China (2020YFB1313900), National Natural Science Foundation of China (61902386), Shenzhen Science and Technology Program (JCYJ20180507182415428).

机构署名：

本校为第一机构

摘要：

Alzheimer's disease (AD) is a degenerative disease of the nervous system. Mild cognitive impairment (MCI) is a condition between brain aging and dementia. The prediction will be divided into stable sMCI and progressive pMCI as a binary task. Structural magnetic resonance imaging (sMRI) can describe structural changes in the brain and provide a diagnostic method for the detection and early prevention of Alzheimer's disease. In this paper, an automatic disease prediction scheme based on MRI was designed. A dense convolutional network was used as ...

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Prediction of Alzheimer's Disease Based on Coordinate-Dense Attention Network

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