Clinically Interpretable Sepsis Early Warning via LLM-Guided Simulation of Temporal Physiological Dynamics

This paper proposes an LLM-guided temporal simulation framework for clinically interpretable early sepsis warning. The model simulates physiological trajectories prior to disease onset by integrating spatiotemporal feature extraction, medical reasoning cues, and agent-based post-processing for physiologically plausible predictions.