Meta Path Guided Graph Attention Network For Explainable Herb

Meta Path Guided Graph Attention Network For Explainable Herb In this paper, we explore the underlying action mechanisms of herbs from both tcm and modern medicine, and propose a meta path guided graph attention network (mgat) to provide the explainable herb recommendations. In this paper, we explore the underlying action mechanisms of herbs from both tcm and modern medicine, and propose a meta path guided graph attention network (mgat) to provide the.

Meta Path Guided Graph Attention Network For Explainable Herb Bibliographic details on meta path guided graph attention network for explainable herb recommendation. Published 2023 view full article home publications publication search publication details title meta path guided graph attention network for explainable herb recommendation authors keywords journal. We utilize attention mechanisms and graph neural networks to capture the correlation between symptoms and herbs. extensive experiments have been done and the results demonstrate the effectiveness of our proposed method. We propose a graph neural network model, mamgn hti, which integrates metapaths with attention mechanisms. a heterogeneous graph consisting of herbs, efficacies, ingredients, and targets is constructed, where semantic metapaths capture latent relationships among nodes.

Meta Path Guided Graph Attention Network For Explainable Herb We utilize attention mechanisms and graph neural networks to capture the correlation between symptoms and herbs. extensive experiments have been done and the results demonstrate the effectiveness of our proposed method. We propose a graph neural network model, mamgn hti, which integrates metapaths with attention mechanisms. a heterogeneous graph consisting of herbs, efficacies, ingredients, and targets is constructed, where semantic metapaths capture latent relationships among nodes. Tl;dr: wang et al. as mentioned in this paper proposed a meta path guided graph attention network (mgat) to provide explainable herb recommendations, which can distill the long range semantics along metapaths and generate fine grained explanations. Any future updates will be listed below meta path guided graph attention network for explainable herb recommendation.