Identification of Dietary Pattern Networks Associated with Gastric Cancer Using Gaussian Graphical Models: A Case-Control Study

Gaussian graphical models (GGMs) are novel approaches to deriving dietary patterns that assess how foods are consumed in relation to one another. We aimed to apply GGMs to identify dietary patterns and to investigate the associations between dietary patterns and gastric cancer (GC) risk in a Korean...

Descripción completa

Detalles Bibliográficos
Autores principales: Gunathilake, Madhawa, Lee, Jeonghee, Choi, Il Ju, Kim, Young-Il, Kim, Jeongseon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7226381/
https://www.ncbi.nlm.nih.gov/pubmed/32340406
http://dx.doi.org/10.3390/cancers12041044

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7226381/
https://www.ncbi.nlm.nih.gov/pubmed/32340406
http://dx.doi.org/10.3390/cancers12041044

Ejemplares similares