Imputing Longitudinal EHR Laboratory Data Under Informative Missingness

This project evaluates practical imputation strategies for longitudinal EHR laboratory data where missingness is associated with clinical visit behavior.

The work is designed to support more reliable downstream subtype discovery and patient-risk characterization in observational health data.

The current page contains a concise background summary; a complete technical write-up will be added later.