NF-GAT: A Node Feature-Based Graph Attention Network for ASD Classification

IF 2.9 Q3 ENGINEERING, BIOMEDICAL

IEEE Open Journal of Engineering in Medicine and Biology Pub Date : 2023-04-26 DOI:10.1109/OJEMB.2023.3267612

Shuaiqi Liu;Beibei Liang;Siqi Wang;Bing Li;Lidong Pan;Shui-Hua Wang

引用次数: 0

Abstract

Goal: The purpose of this paper is to recognize autism spectrum disorders (ASD) using graph attention network. Methods: we propose a node features graph attention network (NF-GAT) for learning functional connectivity (FC) features to achieve ASD diagnosis. Firstly, node features are modelled based on functional magnetic resonance imaging (fMRI) data, with each subject modelled as a graph. Next, we use the graph attention layer to learn the node features and gets the node information of different nodes for ASD classification. Results: Compared with other models, the NF-GAT has significant advantages in terms of classification results. Conclusions: NF-GAT can be effectively used for ASD classification.

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NF-GAT：用于 ASD 分类的基于节点特征的图注意网络

目标：本文旨在利用图注意网络识别自闭症谱系障碍（ASD）。方法：我们提出了一种学习功能连接（FC）特征的节点特征图注意网络（NF-GAT），以实现 ASD 诊断。首先，根据功能磁共振成像（fMRI）数据建立节点特征模型，将每个受试者作为一个图来建模。接下来，我们利用图注意层来学习节点特征，并获取不同节点的节点信息，从而进行 ASD 分类。结果与其他模型相比，NF-GAT 在分类结果方面具有显著优势。结论NF-GAT 可以有效地用于 ASD 分类。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Open Journal of Engineering in Medicine and Biology ENGINEERING, BIOMEDICAL-

CiteScore

9.50

自引率

3.40%

发文量

审稿时长

10 weeks

期刊介绍： The IEEE Open Journal of Engineering in Medicine and Biology (IEEE OJEMB) is dedicated to serving the community of innovators in medicine, technology, and the sciences, with the core goal of advancing the highest-quality interdisciplinary research between these disciplines. The journal firmly believes that the future of medicine depends on close collaboration between biology and technology, and that fostering interaction between these fields is an important way to advance key discoveries that can improve clinical care.IEEE OJEMB is a gold open access journal in which the authors retain the copyright to their papers and readers have free access to the full text and PDFs on the IEEE Xplore® Digital Library. However, authors are required to pay an article processing fee at the time their paper is accepted for publication, using to cover the cost of publication.