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Ai Digital Health

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Research Frontiers in Graph Neural Networks for Disease Pathway Discovery

Applying graph-based deep learning to identify complex biological pathways and protein-interaction networks underlying disease mechanisms.

Topological Dynamics of Multi-Omics Disease Networks
Message Passing Across Temporal Patient Trajectories
Heterogeneous Graph Learning in Drug-Target-Disease Ecosystems
Graph Attention Mechanisms for Causal Pathway Inference
Subgraph Motifs as Biomarkers of Disease Progression
Federated Graph Learning for Privacy-Preserving Phenotyping
Graph Pooling Strategies in Pathway-Level Risk Stratification
Equivariant Neural Networks for Protein-Protein Interaction Graphs
Contrastive Learning on Knowledge Graphs for Drug Repurposing
Graph Autoencoders for Hidden Disease Comorbidity Structures

All AI Digital Health PhD categories