{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,10]],"date-time":"2025-11-10T09:50:24Z","timestamp":1762768224342,"version":"build-2065373602"},"reference-count":73,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T00:00:00Z","timestamp":1762560000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["MTI"],"abstract":"<jats:p>Background: Precision nutrition increasingly integrates mobile health (mHealth) and artificial intelligence (AI) tools. However, personalized hydration remains underdeveloped, particularly in accounting for both food- and beverage-derived water intake. Objective: This scoping review maps the existing literature on mHealth applications that incorporate machine learning (ML) or AI for personalized hydration. The focus is on systems that combine dietary (food-based) and fluid (beverage-based) water sources to generate individualized hydration assessments and recommendations. Methods: Following the PRISMA-ScR guidelines, we conducted a structured literature search across three databases (PubMed, Scopus, Web of Science) through March 2025. Studies were included if they addressed AI or ML within mHealth platforms for personalized hydration or nutrition, with an emphasis on systems using both beverage and food intake data. Results: Of the 43 included studies, most examined dietary recommender systems or hydration-focused apps. Few studies used hydration assessments focusing on both food and beverages or employed AI for integrated guidance. Emerging trends include wearable sensors, AR tools, and behavioral modeling. Conclusions: While numerous digital health tools address hydration or nutrition separately, there is a lack of comprehensive systems leveraging AI to guide hydration from both food and beverage sources. Bridging this gap is essential for effective, equitable, and precise hydration interventions. In this direction, we propose a hydration diet recommender system that integrates demographic, anthropometric, psychological, and socioeconomic data to create a truly personalized diet and hydration plan with a holistic approach.<\/jats:p>","DOI":"10.3390\/mti9110112","type":"journal-article","created":{"date-parts":[[2025,11,10]],"date-time":"2025-11-10T08:57:55Z","timestamp":1762765075000},"page":"112","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Scoping Review of AI-Driven mHealth Systems for Precision Hydration: Integrating Food and Beverage Water Content for Personalized Recommendations"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4967-7798","authenticated-orcid":false,"given":"Kyriaki","family":"Apergi","sequence":"first","affiliation":[{"name":"Department of Food Science and Technology, University of Patras, G Seferi 2, 30100 Agrinio, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4799-4626","authenticated-orcid":false,"given":"Georgios D.","family":"Styliaras","sequence":"additional","affiliation":[{"name":"Department of Food Science and Technology, University of Patras, G Seferi 2, 30100 Agrinio, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"George","family":"Tsirogiannis","sequence":"additional","affiliation":[{"name":"Department of Food Science and Technology, University of Patras, G Seferi 2, 30100 Agrinio, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6896-5218","authenticated-orcid":false,"given":"Grigorios N.","family":"Beligiannis","sequence":"additional","affiliation":[{"name":"Department of Food Science and Technology, University of Patras, G Seferi 2, 30100 Agrinio, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5423-8477","authenticated-orcid":false,"given":"Olga","family":"Malisova","sequence":"additional","affiliation":[{"name":"Department of Food Science and Technology, University of Patras, G Seferi 2, 30100 Agrinio, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,11,8]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2025). 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