Filtering Synthetic Longitudinal Trajectories with Large Language Models as Synthetic Experts

Introduction: Generating synthetic longitudinal data that accurately captures correlation structures within multivariate measurements and over time remains a challenge. When deep learning models are used for synthetic data generation, they often fail to accurately capture clinical patterns. To distinguish [for full text, please go to the a.m. URL]