Machine Learning-Enhanced Patient Risk Prediction Database

Design a Python-based predictive database architecture that integrates machine learning models directly into the database layer for real-time patient risk assessment. Develop a system using SQLAlchemy that can dynamically generate and store predictive models, with support for automatic feature engineering, model versioning, and real-time scoring. The solution must handle complex medical data relationships, support multiple prediction algorithms, and provide transparent model interpretability.