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Nutrients
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Smart Nutrition: Harnessing AI for Personalized Nutrition
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Smart Nutrition: Harnessing AI for Personalized Nutrition

A Special Issue of Nutrients (ISSN 2072-6643) belonging to the section "Nutrition Methodology & Assessment".

Deadline for manuscript submissions: 15 October 2026 | Viewed by 2297

Editor

Prof. Dr. Margaret Allman-Farinelli

E-Mail Website
Guest Editor
Faculty of Medicine and Health, Charles Perkins Centre, The University of Sydney, Camperdown, NSW 2006, Australia
Interests: technology and nutrition; young adults; healthy diets; food security; dietary assessment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The world became aware of artificial intelligence with the public launch of ChatGPT in November 2022. Since then, the growth in AI capabilities has been almost exponential. Nutritionists see multiple and varied uses for their research and translation to professional practice in personalizing nutritional advice. In this Special Issue we want to explore those uses. Manuscripts of interest include using AI to measure and monitor food and beverage consumption. Mining individual data to provide commentary and assessment of diet. This data might be used for AI-generated menus, individually tailored recipes, and suggested swaps of food to improve diet quality. Other areas of interest are the programs and different types of AI that might be used in taking detailed patient histories to tailor advice and the integration of biomedical and social data. Understanding individual food habits and timing of meal ingestion might all be integrated with AI to further personalize nutrition advice. Any use of AI in the prediction of chronic diet-related disease is also of interest, and contributions addressing the ethics and equity of AI-personalized nutrition are welcomed. Original research articles and scoping and systematic reviews are sought.

Prof. Dr. Margaret Allman-Farinelli
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Nutrients is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence
  • generative artificial intelligence
  • machine learning
  • personalized nutrition
  • precision nutrition
  • nutrition care process
  • dietary assessment
  • apps
  • smart devices

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Published Papers (2 papers)

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Research

9 pages, 509 KB  
Article
Validation of a Nutrition Screening Tool in Critically Ill Children
by Anna Burneske, Collin Ellenbecker, Evelyn Kuhn, Jacob Swoveland, Matt Oelstrom, Scott Hagen, Sarah Mandli, Lynne Sears, Jennifer Peterson, Charlene P. Pringle, Kelly Sheridan, Megan Foxe, Abigail Hebron, Elizabeth Zivick, Nicole Fabus, Rebecca Heisler, Melissa Froh, Sadaf Shad and Theresa Mikhailov
Nutrients 2026, 18(14), 2340; https://doi.org/10.3390/nu18142340 - 16 Jul 2026
Viewed by 667
Abstract
Background/Objectives: Malnutrition is prevalent among patients in the pediatric intensive care unit (PICU) and has been shown to worsen in some patients during the PICU stay. In critically ill children, malnutrition is associated with longer PICU length of stay and increased mortality. Several [...] Read more.
Background/Objectives: Malnutrition is prevalent among patients in the pediatric intensive care unit (PICU) and has been shown to worsen in some patients during the PICU stay. In critically ill children, malnutrition is associated with longer PICU length of stay and increased mortality. Several tools have been developed and validated to screen for nutritional status in children, but none were specifically designed for critically ill children. Our study aims to fill this gap. The goal of this study was to refine and validate a novel PICU nutrition screening tool in a diverse population of critically ill children from six PICUs across the United States. Methods: Subjects underwent the nutrition screen and a Subjective Global Nutritional Assessment (SGNA). We used chi-square tests and Mann–Whitney tests to compare elements of the nutrition screen to the SGNA to identify those elements most associated with malnutrition. We used stepwise logistic regression to determine the best fitting model for a malnutrition screening tool. We proposed a scoring system using the factors identified in the best fitting model to define a positive screen. Results: We enrolled 732 subjects at six PICUs. Of these, 131 subjects (17.9%) were malnourished per the SGNA. Children with and without malnutrition did not differ with respect to age, sex, or race. The likelihood of malnutrition increased as weight-for-age percentile decreased (p < 0.001). We found that the best fitting model of a malnutrition screening tool for critically ill children included weight-for-age percentile, cancer, feeding less, parent perception of growth as poor, and being significantly underweight. We defined a positive screen that should prompt referral to a dietitian. Conclusions: We have developed a nutrition screening tool for critically ill children. Full article
(This article belongs to the Special Issue Smart Nutrition: Harnessing AI for Personalized Nutrition)
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14 pages, 883 KB  
Article
Recruitment and Retention of Rural-Dwelling Young Adults into a Digital Healthy Eating Intervention: Lessons Learned from a Randomized Controlled Trial of the Veg4Me Study
by Katherine M. Livingstone, Stephanie R. Partridge, Jonathan C. Rawstorn, Kathleen M. Dullaghan, Yuxin Zhang, Stephanie L. Godrich, Sarah A. McNaughton, Gilly A. Hendrie, Lauren C. Blekkenhorst, Ralph Maddison, John C. Mathers and Laura Alston
Nutrients 2026, 18(11), 1646; https://doi.org/10.3390/nu18111646 - 22 May 2026
Viewed by 737
Abstract
Background/objectives: The study aimed to identify the key methodological challenges and solutions related to recruitment and retention of rural-dwelling young adults into a randomized controlled trial that tests the feasibility of a digital healthy eating intervention (Veg4Me). Methods: Digital registration for [...] Read more.
Background/objectives: The study aimed to identify the key methodological challenges and solutions related to recruitment and retention of rural-dwelling young adults into a randomized controlled trial that tests the feasibility of a digital healthy eating intervention (Veg4Me). Methods: Digital registration for a 12-week study was set up as a one-step process without researcher involvement. Participant registrations and recruitment rates were monitored daily using predetermined online preventative measures to identify fraudulent responses and to amend the digital registration process where necessary. Retention rates were monitored daily to identify any necessary amendments to the follow-up protocol. Results: During data collection, n = 279 fraudulent responses were identified from n = 536 total responses (52%). One month into recruitment, amendments were made to the registration process to reduce fraudulent responses. To address bot attacks, Qualtrics passwords and a two-factor authentication process were added to the Veg4Me landing page. Targeted recruitment strategies, such as unpaid social media posts, corresponded to peaks in recruitment. In the final recruitment month, a question was embedded within follow-up correspondence to encourage completion of the post-intervention survey. This resulted in an additional n = 8 (7%) participants completing the intervention. Conclusions: Empirical observations made in this study suggest that digital recruitment protocols without direct researcher involvement should consider multiple in-built strategies for identifying and preventing fraudulent responses. This includes a two-factor authentication process and minimizing the over-promotion of financial incentives in recruitment strategies. Recruitment strategies should consider the use of social media posts in local community groups, while the use of reminders and notifications could support retention. Full article
(This article belongs to the Special Issue Smart Nutrition: Harnessing AI for Personalized Nutrition)
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