RIDDLE: Race and ethnicity Imputation from Disease history with Deep LEarning

Anonymized electronic medical records are an increasingly popular source of research data. However, these datasets often lack race and ethnicity information. This creates problems for researchers modeling human disease, as race and ethnicity are powerful confounders for many health exposures and tre...

Descripción completa

Detalles Bibliográficos
Autores principales: Kim, Ji-Sung, Gao, Xin, Rzhetsky, Andrey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5940243/
https://www.ncbi.nlm.nih.gov/pubmed/29698408
http://dx.doi.org/10.1371/journal.pcbi.1006106

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5940243/
https://www.ncbi.nlm.nih.gov/pubmed/29698408
http://dx.doi.org/10.1371/journal.pcbi.1006106

Ejemplares similares