Chronic Disease Progression Predictive Modeling

Develop a multi-feature machine learning algorithm that predicts chronic disease progression using heterogeneous medical data sources. The model should integrate electronic health records, genetic markers, lifestyle data, and treatment history with at least 85% accuracy. Create a robust feature engineering approach that handles missing data and accounts for temporal variations in patient health metrics. Include a comprehensive validation methodology that demonstrates model reliability across diverse patient demographics.