A novel pipeline for realistic synthetic longitudinal EHR data generation

Key Points

• Synthetic data generation enhances the realism of longitudinal data models, benefiting research validity.
• The generated electronic health records mimic real patient data, allowing for effective simulations and analyses.
• This assessment employs a novel pipeline that streamlines data generation processes in a systematic manner.
• Overall, this innovative technique may facilitate improved healthcare data analysis, warranting external validation.