ArticleFrontiers in nutrition2022
Dietary Pattern Extraction Using Natural Language Processing Techniques.
Article in Frontiers in nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Integrating patient-reported weight gain cause narratives into personalized obesity management: a data-driven approach with natural language processing and machine learning.Frontiers in nutrition · 2026Article
- Exploring the potential of large language models in nutrition behavior prediction: evidence from college students.Frontiers in nutrition · 2026Article
- Machine Learning-Driven Precision Nutrition: A Paradigm Evolution in Dietary Assessment and Intervention.Nutrients · 2025Review
- Method for predicting the price of carbon based on quadratic decomposition and multiscale prediction.Carbon balance and management · 2025Article
- Foundation models and intelligent decision-making: Progress, challenges, and perspectives.Innovation (Cambridge (Mass.)) · 2025Review
- The impact of online food delivery applications on dietary pattern disruption in the Arab region.Frontiers in public health · 2025Article
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Authors and funding
3 authors.
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Abstract
In this study, we observed the changes in dietary patterns among Korean adults in the previous decade. We evaluated dietary intake using 24-h recall data from the fourth (2007-2009) and seventh (2016-2018) Korea National Health and Nutrition Examination Survey. Machine learning-based methodologies were used to extract these dietary patterns. Particularly, we observed three dietary patterns from each survey similar to the traditional and Western dietary patterns in 2007-2009 and 2016-2018, respectively. Our results reveal a considerable increase in the number of Western dietary patterns compared with the previous decade. Thus, our study contributes to the use of novel methods using natural language processing (NLP) techniques for dietary pattern extraction to obtain more useful dietary information, unlike the traditional methodology.
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