Multi-Dimensional Healthcare Readmission Risk Model

Develop a comprehensive Python-based predictive model for hospital readmission risk using complex medical datasets. Integrate electronic health record features, socioeconomic indicators, treatment history, and demographic data. Implement advanced ensemble machine learning techniques including gradient boosting and neural networks to create a robust predictive framework. The model must handle imbalanced medical data, provide interpretable risk factors, and generate actionable insights for healthcare providers.