This paper is in the following e-collection/theme issue:

Viewpoints and Perspectives (514) Food Sciences and Nutrition Engineering (54)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37667, first published .
Design Issues in Personalized Nutrition Advice Systems

Design Issues in Personalized Nutrition Advice Systems

Design Issues in Personalized Nutrition Advice Systems

Authors of this article:

Iris M de Hoogh1, 2 Author Orcid Image ;   Machiel J Reinders3 Author Orcid Image ;   Esmée L Doets4 Author Orcid Image ;   Femke P M Hoevenaars1 Author Orcid Image ;   Jan L Top4 Author Orcid Image
Article Authors Cited by (6) Tweetations (7) Metrics

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  2. Papastratis I, Konstantinidis D, Daras P, Dimitropoulos K. AI nutrition recommendation using a deep generative model and ChatGPT. Scientific Reports 2024;14(1) View
  3. Jospe M, Richardson K, Saleh A, Bohlen L, Crawshaw J, Liao Y, Konnyu K, Schembre S. Leveraging continuous glucose monitoring as a catalyst for behaviour change: a scoping review. International Journal of Behavioral Nutrition and Physical Activity 2024;21(1) View
  4. Atampugbire G, Adomako E, Quaye O. Medicinal Plants as Effective Antiviral Agents and Their Potential Benefits. Natural Product Communications 2024;19(9) View
  5. Yang L, Guo Z, Xu X, Kang H, Lai J, Li J. An Online Multimodal Food Data Exploration Platform for Specific Population Health: Development Study. JMIR Formative Research 2024;8:e55088 View
  6. Gimpfl S, Steinle K, Gedrich K. Evaluating Various Methods Used by Direct-to-Consumer Products Promising Personalized Nutrition. Dietetics 2024;3(4):504 View