Machine Learning Feature Engineering for Predictive Healthcare Diagnostics

Develop a generalized feature selection and engineering framework for medical diagnostic prediction models that can automatically handle heterogeneous medical datasets. Create modular preprocessing pipelines that can intelligently handle missing data, normalize different measurement scales, and generate meaningful synthetic features using domain-aware transformations. Include statistical significance testing and feature importance ranking mechanisms.