Predictive Clinical ML Sidecar

Architecture

• Framework: Python FastAPI sidecar running an optimized gradient boosted tree model (LightGBM/XGBoost).
• Inputs: 15-minute sliding windows of normalized heart rate, SpO2, blood pressure, and core temperature.
• Output: Decompensation probability ($0.0$ to $1.0$) and dominant clinical risk factor.