Metabolic Phenotype Modelling and Dietary Personalisation: Machine Learning Frameworks for Evidence-Based Nutrition and Lifestyle Intervention Optimisation

Authors

  • Juan Gómez-Olmos Associate Professor of Computer Science, University of Jaén

Keywords:

metabolic phenotype modelling, dietary personalisation, machine learning frameworks, evidence-based nutrition

Abstract

Because of the substantial variation in individual responses to diet and lifestyle interventions, tailoring health recommendations on the basis of individual profiles is becoming increasingly popular. An important asset of personalizing recommendations is the ability to respect how people live, rather than trying to change their behaviors to fit the much more generic approach of one-size-fits-all intervention programs.

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Published

30-06-2025

How to Cite

[1]
“Metabolic Phenotype Modelling and Dietary Personalisation: Machine Learning Frameworks for Evidence-Based Nutrition and Lifestyle Intervention Optimisation”, Blockchain Tech. & Distributed Sys., vol. 5, no. 1, pp. 22–30, Jun. 2025, Accessed: Jun. 05, 2026. [Online]. Available: https://thesciencebrigade.com/btds/article/view/855