ADS Capstone Chronicles Revised

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glucose management, exercise, medication, and nutrition. While dietary needs are unique to the individual, general guidelines recommend standard healthy eating practices including non starchy vegetables, lean or plant-based sources of protein, and limiting added sugar and processed foods (American Diabetes Association, 2024). By combining dietary recommendations and restaurant menu nutritional information with individual patient health data, there is an opportunity to create a system that supports diabetes management preemptively. The purpose of this work is to establish a food recommendation system for individuals with diabetes, allowing them to make informed dietary decisions at their preferred restaurants. The simplification of this process for those with unique dietary restrictions is designed to provide an easy, stress-free dining experience while maintaining health goals. It is hypothesized that physical

diabetic users will be able to make more informed dining choices, aiming to stabilize post meal glucose levels. This system will leverage glycemic load, carbohydrate content, and individual preferences to suggest meals that minimize the risk of glucose spikes. Through data analysis and implementation of various data science methods, this project seeks to uncover underlying patterns in the health of individuals with diabetes and increase the transparency of restaurant food nutrition facts to provide the best recommendations. The project will follow the data lifecycle illustrated in Figure 1. As a result, people intending to follow specific dietary guidelines and manage their diabetes will have access to a comprehensive system that not only provides them with food recommendations, but is tailored to their unique goals and preferences. Outside of food recommendations, this system will also provide the user with the ability to determine how the food they want to eat may affect glucose levels.

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