The introduction of KAT-GNN, a Knowledge-Augmented Temporal Graph Neural Network, marks a significant advancement in clinical risk prediction using electronic health records (EHRs). This innovative framework addresses the complexities of modeling diverse and irregular temporal EHR data, which is crucial for timely medical interventions and informed clinical decision-making. By integrating clinical knowledge with temporal dynamics, KAT-GNN enhances the accuracy of risk predictions, potentially improving patient outcomes and streamlining healthcare processes.