Machine Learning Feature Engineering for Disease Prediction

Design a complex SQL query that prepares feature vectors for machine learning disease prediction models. The query must transform raw medical data into normalized, machine-learning-ready features, including feature engineering for comorbidity indicators, medication interaction risks, and predictive health markers. Implement advanced normalization techniques, handle missing data intelligently, and create a feature matrix that can be directly imported into Python or R for predictive modeling.