Article

The Synthetic Fidelity–Stability Framework (SFSF): A Systematic Multi-Dimensional Benchmark of Synthetic Clinical Laboratory Data Generators

2026-08-12

Abstract excerpt

<h4>Background</h4> Synthetic data generation is increasingly proposed as a strategy to support privacy-preserving data sharing, augmentation of small or restricted biomedical datasets, and benchmarking of artificial intelligence tools in laboratory medicine. However, model selection remains difficult because synthetic data generators differ in fidelity, privacy risk, stability, and generalisability. Existing eva...

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Literature Corpus work: a881886f-aa17-5cc8-ab7b-aab4d51d322e
DOI: 10.64898/2026.08.11.741471

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