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This is a Systematic Review study.

Methods for Generating and Evaluating Synthetic Longitudinal Patient Data: A Systematic Review

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Synthetic data generation methods were systematically reviewed to generate longitudinal patient data.
The review identified 39 methods addressing aspects like temporal structure and unbalanced data.
Evaluation criteria were highlighted as critical for assessing the resemblance and utility of synthetic patient data.
Further development in privacy-preserving synthetic methods is needed to enhance real-world application.

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Systematic review uncovers methods for synthetic data generation in patient care, highlighting data security and evaluation challenges.

Perkonoja et al. (2025) studied this question.

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