Variational Autoencoder Modular Bayesian Networks (VAMBN) for Simulation of Heterogeneous Clinical Study Data
Luise Gootjes-Dreesbach, Meemansa Sood, Akrishta Sahay, Martin Hofmann‐Apitius, Holger Fröhlich
This paper introduces VAMBN, a variational autoencoder modular Bayesian network for simulating realistic clinical study data while ensuring privacy and enabling counterfactual scenarios.
Frontiers in Big Data · May 28, 2020Peer-reviewedBioinformatics