Generation of synthetic medical data KU Leuven
Generating realistic synthetic data that preserves all properties without sharing any individualized information proves to be extremely challenging in practice. There is no single fit-for-all approach that can generate the optimal synthetic data in all scenarios, and one must consider the ensuing problem at hand and the tentative analysis approach before choosing the suitable data generating methods. In the context, we will investigate the ...