Article

A Multidimensional Evaluation of Privacy-Preserving Generative Models for Neonatal Clinical Tabular Data: Fidelity, Utility, and Realism Trade-offs

2026-01-21

Abstract excerpt

<title>Abstract</title> <p>Background The limited availability of neonatal clinical data due to privacy constraints, small sample sizes, and severe class imbalance poses significant challenges for data-driven medical research. Privacy-preserving synthetic data generation has emerged as a promising solution; however, the relative performance of different generative models for neonatal tabular data remains insuffi...

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Literature Corpus work: 440c0891-6e7b-5896-af92-acf659292405
DOI: 10.21203/rs.3.rs-8580093/v1

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