HIPAA-Compliant Patient Risk Stratification Model

Develop a machine learning pipeline using Python that predicts high-risk patient cohorts for preventive interventions while maintaining strict HIPAA data anonymization. The model should integrate patient historical data from electronic health records (EHR), including ICD-10 codes, medication history, and demographic information. Implement differential privacy techniques using PySyft to ensure patient data confidentiality. The output should be a risk score between 0-1 with explainable AI components that healthcare providers can interpret.