ArticleCancers2020
Identification of Dietary Pattern Networks Associated with Gastric Cancer Using Gaussian Graphical Models: A Case-Control Study.
Article in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
9 citing papers in PubMed, 15 citations in OpenAlex.
- Associations between Dietary Pattern Networks Derived from Machine Learning Algorithms and Cardiovascular Disease Risk in the NutriNet-Santé Cohort.The Journal of nutrition · 2025Observational
- Unveiling Dietary Complexity: A Scoping Review and Reporting Guidance for Network Analysis in Dietary Pattern Research.Nutrients · 2025Article
- Dietary patterns derived by Gaussian graphical models and metabolic profiles among overweight and obese individuals.Scientific reports · 2025Article
- Sex-specific associations of empirically derived dietary patterns with colorectal cancer risk in a Korean population: a case‒control study.Scientific reports · 2024Article
- Network analysis of psychological factors related to academic pressure faced by medical students in the central and highland regions of Vietnam.Medical education online · 2022Article
- Seaweed and Iodine Intakes and SLC5A5 rs77277498 in Relation to Thyroid Cancer.Endocrinology and metabolism (Seoul, Korea) · 2022Article
- Effect of the Interaction between Dietary Patterns and the Gastric Microbiome on the Risk of Gastric Cancer.Nutrients · 2021Article
- Article
- The Role of Dyslipidemia in Colitis-Associated Colorectal Cancer.Journal of oncology · 2021Review
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
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 population. In this case-control study of 415 GC cases and 830 controls, food intake was assessed using a 106-item semiquantitative food frequency questionnaire that captured 33 food groups. The dietary pattern networks corresponding to the total population contained a main network and four subnetworks. For the vegetable and seafood network, those who were in the highest tertile of the network-specific score showed a significantly reduced risk of GC both in the total population (OR = 0.66, 95% CI = 0.47-0.93,
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.