Multivariate time series clustering analysis of the Global Dietary Database to uncover patterns in dietary trends (1990–2018)

Multivariate time series clustering analysis of the Global Dietary Database to uncover patterns in dietary trends (1990–2018)

Abstract Objective: Understanding country-level nutrition intake is crucial to global nutritional policies that aim to reduce disparities and relevant disease burdens. Still, there are limited numbers of studies using clustering techniques to analyse the recent Global Dietary Database (GDD). This...

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Bibliographic Details
Main Authors: Adriano Matousek, Tiffany H Leung, Herbert Pang
Format: Article
Language:English
Published: Cambridge University Press 2025-01-01
Series:Public Health Nutrition
Subjects:
Clustering algorithm
Machine learning
Time-series clustering
Trend
Global Dietary Database
Online Access:https://www.cambridge.org/core/product/identifier/S136898002500059X/type/journal_article
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