DHCLHAM: microbe-drug interaction prediction based on dual-hypergraph contrastive learning framework with hierarchical attention mechanism

A computational framework was developed through multi-dimensional case validation, integrating artificial intelligence and network pharmacology principles, offering a novel paradigm for analyzing microbe-drug interaction mechanisms. The research findings hold significant reference value for optimizing clinical treatment protocols and establish a theoretical foundation to develop precise medication strategies aimed at intestinal flora.