Diet4You: a personal intelligent recommender for diets from a holistic perspective
| Autor: | Gibert, Karina, Sevilla-Villanueva, Beatriz, Sànchez-Marrè, Miquel, Marqués, Lluís, Casanova, Èric, Fitó Colomer, Montse |
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| Přispěvatelé: | Universitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa, Universitat Politècnica de Catalunya. Departament de Ciències de la Computació, Universitat Politècnica de Catalunya. KEMLG - Grup d'Enginyeria del Coneixement i Aprenentatge Automàtic |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Artificial intelligence
Knowledge management Intel·ligència artificial Personalized Recommendation Personalized Medicine Matemàtiques i estadística::Matemàtica aplicada a les ciències [Àrees temàtiques de la UPC] Casebased reasoning 62 Statistics::62D05 Sampling theory sample surveys [Classificació AMS] 68 Computer science::68T Artificial intelligence [Classificació AMS] Data science Contextual information Matemàtiques i estadística::Estadística aplicada [Àrees temàtiques de la UPC] Nutritional Plan Prescription Sampling (Statistics) Healthy lifestyles Mostreig (Estadística) |
| Zdroj: | UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) |
| Popis: | Prevention and nutrition are key for healthy lifestyles and are crucial in the new paradigm of patient-centered medicine, as healthy diet protects against chronic diseases and helps to delay diseases in general population. Making healhty diets is becoming essential and there are no well-formalized support mechanisms for suporting nutritionists when designing diets of specific patients. The project Diet4You proposes an intelligent decision support system oriented to the adaptive and dynamic preparation of personalized diets for specific individuals from general population, with or without comorbidities. Diet4You is a hybrid system interacting several AI and data science components in a complex way to compose diets by taking into account all the information available on the person, including their characteristics, health conditions, personal and cultural habits and eventual drugs intake and their genomic information. Authors are not aware of other menus recommenders with such a holistic view. The system is highly configurable. It relies on an information system that can formalize all contextual knowledge to improve optimization, and the menus are composed over a food database containing prepared dishes with known nutritional decomposition. This work has been partially supported by project Diet4You (TIN2014-60557-R), and the Consolidated Research Group Grant from AGAUR (Generalitat de Catalunya, cataalan government) IDEAI-UPC (AGAUR SGR2017-574). |
| Databáze: | OpenAIRE |
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