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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...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2020
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| Materias: | |
| 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 |