The validity of synthetic clinical data: a validation study of a leading synthetic data generator (Synthea) using clinical quality measures

BACKGROUND: Clinical data synthesis aims at generating realistic data for healthcare research, system implementation and training. It protects patient confidentiality, deepens our understanding of the complexity in healthcare, and is a promising tool for situations where real world data is difficult...

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Detalles Bibliográficos
Autores principales: Chen, Junqiao, Chun, David, Patel, Milesh, Chiang, Epson, James, Jesse
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6416981/
https://www.ncbi.nlm.nih.gov/pubmed/30871520
http://dx.doi.org/10.1186/s12911-019-0793-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6416981/
https://www.ncbi.nlm.nih.gov/pubmed/30871520
http://dx.doi.org/10.1186/s12911-019-0793-0

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