Generating synthetic mixed discrete-continuous health records with mixed sum-product networks.
Privacy is a concern whenever individual patient health data is exchanged for scientific research. We propose using mixed sum-product networks (MSPNs) as private representations of data and take samples from the network to generate synthetic data that can be shared for subsequent statistical analysis. This anonymization method was evaluated with respect to privacy and information loss.
Author(s): Kroes, Shannon K S, van Leeuwen, Matthijs, Groenwold, Rolf H H, Janssen, Mart P
DOI: 10.1093/jamia/ocac184