Preliminary Results of Intelligent Model for Food Recommendation Consumption in Adults

This research addresses the problems that exist in relation to poor nutrition and the health consequences that this entails. Its development is based on the generation of a healthy food recommendation algorithm. Recommendation algorithms (AR) are defined as a system that produces a recommendation based on an analysis of user preferences and needs, and in the field of food, a tool for decision support when receiving a recommendation and providing knowledge basic in order to making decisions when consuming food. In this sense, due to the importance of taking into consideration the health conditions of the user, their preferences, culture, and lifestyle, this work aims to develop an AR of healthy foods that is a tool to support decision-making decisions. Finally, for this first stage of the investigation, tests were carried out with real users that allowed them to verify the veracity of the proposed model, giving satisfactory results, which nods to the next stage of development that will involve cultural aspects, and health, among others.