Artificial Intelligence and Personalized Nutrition: How Algorithms Facilitate Balanced Macro-and Micronutrient Intake
Résumé
The rapid convergence of nutrition science and artificial-intelligence (AI) engineering is enabling menu-planning systems that dynamically satisfy population dietary guidelines while adapting to the metabolic, genetic and behavioural diversity of individuals. Contemporary studies show that algorithm-generated menus can remain within the Acceptable Macronutrient Distribution Ranges (AMDRs) and micronutrient reference values, predict post-prandial responses, and reduce cardiometabolic risk markers more effectively than generic advice. Smartkitchen appliances and inventory-aware shopping lists further close the loop by cutting food waste and cost. Yet, these benefits arrive with regulatory and ethical responsibilities around data privacy and algorithmic fairness. The article below reviews the scientific foundations, digital workflows and clinical evidence underlying AI-driven personalised menu generation and identifies research priorities for the coming decade.
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