Patient Treatment Response Prediction Model

Design a sophisticated machine learning model to predict individual patient treatment responses using multi-modal data sources. Develop an approach that integrates genetic information, historical treatment data, lifestyle factors, and real-time health metrics to generate personalized treatment response probabilities. Implement advanced feature engineering techniques and use interpretable machine learning models like gradient boosting or neural networks with attention mechanisms. The solution must provide both predictive accuracy and model explainability.