Dynamic Viewing Pattern Analysis: Towards Large-Scale Screening of Children with ASD in Remote Areashttps://www.embs.org/tbme/wp-content/uploads/sites/19/2023/04/TBME-01073-2022-Website_Image.jpg789444IEEE Transactions on Biomedical Engineering (TBME)IEEE Transactions on Biomedical Engineering (TBME)//www.embs.org/tbme/wp-content/uploads/sites/19/2022/06/ieee-tbme-logo2x.png
This study has discovered an effective viewing feature for identifying children with ASD and developed an intelligent classification model. It provides powerful support for low-cost and non-invasive ASD screening.
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Constructing Multi-view High-order Functional Connectivity Networks for Diagnosis of Autism Spectrum Disorderhttps://www.embs.org/tbme/wp-content/uploads/sites/19/2022/02/TBME-02224-2020-Highlight-Image-1.gif213177IEEE Transactions on Biomedical Engineering (TBME)IEEE Transactions on Biomedical Engineering (TBME)//www.embs.org/tbme/wp-content/uploads/sites/19/2022/06/ieee-tbme-logo2x.png
To fully explore the discriminative information provided by different brain networks, a cluster-based multi-view high-order FCN (Ho-FCN) framework is proposed in this paper. Specifically, we first group the functional connectivity (FC) time series into different clusters and compute the multi-order central moment series for the FC time series in each cluster. Then we utilize the correlation of central moment series between different clusters to reveal the high-order FC relationships among multiple ROIs.
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