An Interpretable Population Graph Network to Identify Rapid Progression of Alzheimer’s Disease Using UK Biobank

This study proposes an interpretable population graph network framework for identifying rapid progressors of Alzheimer’s Disease by utilizing patient information from electronic health-related records in the UK Biobank. The framework creates a patient similarity graph where each AD patient is represented as a node with edges established by clinical characteristics distance, using graph neural networks (GNNs) and a GNN Explainer with SHAP analysis for interpretability.