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A visualization tool was also developed to highlight influential network members for each individual within the multiple social networks. The multigraph GAT-HIV models obtained average AUC values of 0.776 and 0.824 for Chicago and Houston, respectively, performing better than empirical predictive models (e.g. AUCs of random forest 0.758 and 0.798). GAT-HIV on single networks also delivered promising prediction performances. The proposed methods provide a comprehensive and interpretable framework for graph-based model

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