Cargando…
Variational Autoencoder Modular Bayesian Networks for Simulation of Heterogeneous Clinical Study Data
In the area of Big Data, one of the major obstacles for the progress of biomedical research is the existence of data “silos” because legal and ethical constraints often do not allow for sharing sensitive patient data from clinical studies across institutions. While federated machine learning now all...
Autores principales: | Gootjes-Dreesbach, Luise, Sood, Meemansa, Sahay, Akrishta, Hofmann-Apitius, Martin, Fröhlich, Holger |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7931863/ https://www.ncbi.nlm.nih.gov/pubmed/33693390 http://dx.doi.org/10.3389/fdata.2020.00016 |
Ejemplares similares
-
Realistic simulation of virtual multi-scale, multi-modal patient trajectories using Bayesian networks and sparse auto-encoders
por: Sood, Meemansa, et al.
Publicado: (2020) -
Improving Variational Autoencoders for New Physics Detection at the LHC With Normalizing Flows
por: Jawahar, Pratik, et al.
Publicado: (2022) -
Editorial: Bayesian Inference and AI
por: Tang, Niansheng, et al.
Publicado: (2022) -
Coming Together of Bayesian Inference and Skew Spherical Data
por: Nakhaei Rad, Najmeh, et al.
Publicado: (2022) -
Bayesian Joint Modeling of Multivariate Longitudinal and Survival Data With an Application to Diabetes Study
por: Huang, Yangxin, et al.
Publicado: (2022)