Recommender system for healthy food choices

Recommender system for healthy food choices

A recommender system that proposes the right meal at the right time based on your biomarkers and contextual information? That is the challenge that this research project is tackling together with Clear. Clear is a startup in nutrition precision and has a unique dataset of user demographics, logged meals and postprandial glucose values of these meals. The existing data confirms what is known from recent literature: people can respond differently to the same meals. This highlights the complexity of individual dietary responses and underscores the need for a personalized approach to meal recommendations.

Several specific challenges must be addressed for the successful development of a recommender system that goes beyond conventional dietary guidance. For instance, can the system accurately predict glucose values after a meal based on factors such as previous glucose measurements, user demographics, and meal composition alone? Additionally, can the system identify similar responses to meals among different users? Finally, the project aims to determine how to translate the outcomes of the predictive model into a recipe recommender system. This system would consider not only physiological data but also user preferences, allergies, and contextual information.

Researchers: Hanna Hauptmann, Christine Bauer
Partner: Clear B.V.

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