Intelligent Meal Planning: Algorithmic Inclusion of Kefir in Nutritional Recommendations
Main Article Content
Abstract
This study employs advanced machine learning techniques to systematically analyze comprehensive nutritional data from the Food and Nutrient Database for Dietary Studies (FNDDS), focusing on dairy products. The primary goal is to distinguish the nutritional profiles of fermented dairy foods, such as kefir and yogurt, from non-fermented dairy counterparts, like milk and cream. Leveraging a robust dataset encompassing detailed nutrient information, this research aims to identify unique nutritional characteristics inherent to fermented dairy products that may contribute significantly to dietary interventions aimed at health enhancement and chronic disease prevention. Findings from this analysis offer practical insights for dietary planning, emphasizing evidence-based nutritional recommendations, and underscore the critical role of fermented dairy in personalized healthcare strategies.
Article Details
The Medical Research Archives grants authors the right to publish and reproduce the unrevised contribution in whole or in part at any time and in any form for any scholarly non-commercial purpose with the condition that all publications of the contribution include a full citation to the journal as published by the Medical Research Archives.
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