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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...
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| Pubblicato in: | Cancers (Basel) |
|---|---|
| Autori principali: | , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7226381/ https://ncbi.nlm.nih.gov/pubmed/32340406 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/cancers12041044 |
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