3 papers
cs.LG2026
Evaluating quality in synthetic data generation for large tabular health datasets
Jean-Baptiste Escudié, Benjamin Barnes, Stefan Meisegeier +3
There is no consensus in the field of synthetic data on concise metrics for quality evaluations or benchmarks on large health datasets, such as historical epidemiological data. Thi…
eess.IV2026
Explainable histomorphology-based survival prediction of glioblastoma, IDH-wildtype
Jan-Philipp Redlich, Friedrich Feuerhake, Stefan Nikolin +12
Glioblastoma, IDH-wildtype (GBM-IDHwt) is the most common malignant brain tumor. While histomorphology is a crucial component of GBM-IDHwt diagnosis, it is not further considered f…
cs.LG2025
Automatic Extraction of Rules for Generating Synthetic Patient Data From Real-World Population Data Using Glioblastoma as an Example
Arno Appenzeller, Nick Terzer, André Homeyer +10
The generation of synthetic data is a promising technology to make medical data available for secondary use in a privacy-compliant manner. A popular method for creating realistic p…