scKDGM proposes a KAN-guided dynamic graph masked learning framework with GDP-Mask, TAKGCN encoder, mask-guided recovery, cross-view contrastive learning and ZINB loss that outperforms 10 baselines on 12 scRNA-seq datasets in NMI and ARI.
A node-collaboration-informed graph convolutional network for highly accurate representation to undirected weighted graph,
2 Pith papers cite this work. Polarity classification is still indexing.
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The system integrates a Neo4j knowledge graph, four-stage symptom matching with LLM verification, genetic-algorithm-optimized proactive questioning, and multimodal evidence-based visualizations to improve diagnostic transparency and treatment interpretability in TCM, reporting 32% fewer non-standard
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Evidence-Based Intelligent Diagnostic and Therapeutic Visualization System with Large Language Models: Multi-Turn Interaction and Multimodal Treatment Plan Generation
The system integrates a Neo4j knowledge graph, four-stage symptom matching with LLM verification, genetic-algorithm-optimized proactive questioning, and multimodal evidence-based visualizations to improve diagnostic transparency and treatment interpretability in TCM, reporting 32% fewer non-standard