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The study presents the EEG Mind-Transformer, a novel deep learning architecture designed for enhanced EEG analysis in mental health monitoring. This model incorporates a Dynamic Temporal Graph Attention Mechanism, a Hierarchical Graph Representation and Analysis module, and a Spatial-Temporal Fusion Module, significantly improving classification accuracy and generalizability across diverse mental health conditions. Empirical results demonstrate its superiority over traditional methods, achieving high accura
- Author
- yusrairshadali505
- Language
- EN