Machine Learning Feature Store for Clinical Predictions

Develop a distributed feature store using Node.js and Redis that supports machine learning model training for clinical predictive analytics. Design a system that can efficiently store, version, and retrieve complex medical feature sets, with built-in support for feature engineering pipelines. Implement a versioning mechanism that allows models to be trained and compared using consistent feature representations across different research iterations.