Patient Readmission Risk Prediction Framework

Create an advanced machine learning pipeline using XGBoost to predict hospital readmission risks with high accuracy. The model should: 1) Process complex medical feature sets including ICD-10 codes, medication history, and demographic data, 2) Implement advanced feature engineering techniques, 3) Generate explainable AI reports detailing risk factors, 4) Provide real-time scoring API for clinical decision support, and 5) Include comprehensive model performance tracking and drift detection.