Data-driven food recommendations for reducing physiological dysregulation

Personalized nutrition and dietary recommendation products claiming to improve health are moving faster than the underlying science. Existing tools for communicating healthy foods are available, but they are designed for public (not individual) health, can not incorporate diet history, and can not adapt to the user’s preferred health outcomes. We propose to implement and fine-tune our previously developed system for creating personalized food recommendations to increase health using cross-sectional dietary recall and blood biomarker data from the National Health and Nutrition Examination Survey (NHANES). The partner organization and the academic institution will provide ease-of-access to and previous experience with these data, and the intern will be performing the analyses. The partner organization will benefit by being able to include these data driven food recommendations on their health platform.

Faculty Supervisor:

Félix Camirand Lemyre

Student:

Partner:

Oken Health

Discipline:

Life Sciences

Sector:

Education; Professional, scientific and technical services

University:

Université de Sherbrooke

Program: