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