An AI-based nutrition recommendation system: technical validation with insights from Mediterranean cuisine
With solid accuracy in filtering, diversity, and caloric/macronutrient suggestions, the proposed system offers a promising solution to modern dietary challenges.
Authors
- Metin Güldaş (ORCID: https://orcid.org/0000-0002-5187-9380)
- Noemí Boqué (ORCID: https://orcid.org/0000-0001-7173-5512)
- Lazaros Gymnopoulos (ORCID: https://orcid.org/0000-0003-3310-102X)
- Lorena Calderón-Pérez (ORCID: https://orcid.org/0000-0003-0766-0733)
- Kosmas Dimitropoulos (ORCID: https://orcid.org/0000-0003-1584-7047)
- Cevdet Demir (ORCID: https://orcid.org/0000-0002-9381-0410)
- Kyriakos Kalpakoglou (ORCID: https://orcid.org/0009-0004-4117-0281)
Institutions
- Bursa Uludağ Üni̇versi̇tesi̇ (TR)
- Information Technologies Institute (GR)
- Technological Center of Nutrition and Health (ES)
- Centre for Research and Technology Hellas (GR)
Publication Details
- Journal
- Frontiers in Nutrition
- Published
- 2025-08-14
- DOI
- https://doi.org/10.3389/fnut.2025.1546107
- Citations
- 9
- Primary Topic
- Nutritional Studies and Diet
- Type
- article
- Field-Weighted Citation Impact
- 16.91
Funders
- European Commission