NetFeatures-Transformer: Enhancing Brain Network Features to Classify Alzheimer's Disease-Reference-Cited by-同舟云学术

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NetFeatures-Transformer: Enhancing Brain Network Features to Classify Alzheimer's Disease

Published:2023-10-26 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)
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Author:

Cao Yu¹,Kuai Hongzhi²,Zhong Ning²,Wang Bixin³,Fan Fengmei³,Yan Jianzhuo¹

Affiliation:

1. Beijing University of Technology,Faculty of Information Technology,Beijing,China

2. Maebashi Institute of Technology,Faculty of Engineering,Maebashi, Gunma,Japan

3. Peking University, Huilongguan Clinical Medical School,Beijing Huilongguan Hospital,Beijing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10350035/10350061/10350162.pdf?arnumber=10350162

Reference16 articles.

1. Brain Informatics

2. Web Intelligence meets Brain Informatics: Towards the future of artificial intelligence in the connected world

3. Functional MRI, resting state fMRI, and DTI for predicting verbal fluency outcome following resective surgery for temporal lobe epilepsy

4. Four-way classification of Alzheimer’s disease using deep Siamese convolutional neural network with triplet-loss function

5. THINKING-LOOP: The Semantic Vector Driven Closed-Loop Model for Brain Computing

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Transformer’s Role in Brain MRI: A Scoping Review;IEEE Access;2024

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