ArticleJournal of agricultural and food chemistry2026
Simulation of the Metabolic Response to an Interventional Study with New Healthy Beverages by Machine-Learning Regression.
Article in Journal of agricultural and food chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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Authors and funding
4 authors.
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Abstract
The present study proposes a methodology to emulate an interventional trial by employing machine-learning (ML) models. A maqui-citrus beverage is used as a case study, exploiting empirical data to assess the performance of multiple ML algorithms, to further build regression models. Those models predicted the effect of consuming the beverage for 60 days, sweetened with different sweeteners, on flavanones and their metabolites and anthocyanin metabolites present in plasma and urine. To guarantee the reliability of the predictions, a comprehensive data analysis and preprocessing was carried out, followed by a hyperparameter tuning using Bayesian optimization. The models were benchmarked, yielding a goodness of fit
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Registered trials
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