Translational Algorithms for Technological Dietary Quality Assessment Integrating Nutrimetabolic Data with Machine Learning Methods

Recent advances in machine learning technologies and omics methodologies are revolutionizing dietary assessment by integrating phenotypical, clinical, and metabolic biomarkers, which are crucial for personalized precision nutrition. This investigation aims to evaluate the feasibility and efficacy of...

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Bibliographic Details
Published in:	Nutrients Vol. 16; no. 22; p. 3817
Main Authors:	de la O, Víctor, Fernández-Cruz, Edwin, Matía Matin, Pilar, Larrad-Sainz, Angélica, Espadas Gil, José Luis, Barabash, Ana, Fernández-Díaz, Cristina M., Calle-Pascual, Alfonso L., Rubio-Herrera, Miguel A., Martínez, J. Alfredo
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 07.11.2024 MDPI
Subjects:	Algorithms Artificial intelligence Biomarkers Eating Feasibility Studies Food habits Humans Machine Learning Metabolites Methods Nutrition Nutrition Assessment Nutrition research Political aspects Product/Service Evaluations ROC Curve Type 2 diabetes Taiwan Spain dietary assessment machine learning computational algorithm precision nutrition clinical biomarkers nutritional evaluation
ISSN:	2072-6643, 2072-6643
Online Access:	Get full text
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