The use of machine learning algorithms in the field of nutritional health is a topic that has been developed in recent years for the early diagnosis of diseases or the recommendation of better nutritional habits. People with poor diets are more prone to chronic diseases and, in the long term, this can lead to dead. This study proposes a model for the recommendation of nutritional plans using the decision tree technique considering the patient data, in complement with the BMI (Body Mass Index) and BMR (Basal Metabolic Rate) to evaluate and recommend the best nutritional plan for the patient. The algorithm used in the model was trained with a dataset of meal plan data assigned by specialists which were obtained from the Peruvian food composition table, and the data from the diets that were assigned and collected from the nutrition area of the Hospital Marino Molina Sccipa in Lima, Peru. Pr...

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.