Food Clustering Analysis for Personalized Food Replacement

Abstract

Everybody needs a balanced diet to maintain a healthy body. An unbalanced diet may lead to disease and sickness. Medical nutrition therapy (MNT) is important in preventing diabetes, managing existing diabetes, and preventing, or at least slowing, the rate of development of diabetes complications. The most common way for Diabetes Educators to inform diabetes patients of their nutrition therapy is by introducing food substitution. Patients are taught to replace food items from the same food group based on the quantity of the desired nutrients. However, this method may not provide the best results because it does not accurately take into account of all the food characteristics, diabetes diet-care requirements, and the relationships between the different types of food. The goal of our study is to propose a food clustering analysis mechanism for personalized food replacement and recommendation. Our proposed approach will be helpful to nutritionists in creating new food groups and personalized food replacements and recommendations.