Published on in Vol 3, No 4 (2019): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12966, first published .
A Mobile Phone App for the Provision of Personalized Food-Based Information in an Eating-Out Situation: Development and Initial Evaluation

A Mobile Phone App for the Provision of Personalized Food-Based Information in an Eating-Out Situation: Development and Initial Evaluation

A Mobile Phone App for the Provision of Personalized Food-Based Information in an Eating-Out Situation: Development and Initial Evaluation

Journals

  1. Wei Y, Zheng P, Deng H, Wang X, Li X, Fu H. Design Features for Improving Mobile Health Intervention User Engagement: Systematic Review and Thematic Analysis. Journal of Medical Internet Research 2020;22(12):e21687 View
  2. Komatsu H, Watanabe E, Fukuchi M. Psychiatric Neural Networks and Precision Therapeutics by Machine Learning. Biomedicines 2021;9(4):403 View
  3. Conde-Caballero D, Jiménez B, Juarez L. Memories of Hunger, Continuities, and Food Choices: an Ethnography of the Elderly in Extremadura (Spain). Appetite 2021:105267 View
  4. Flaherty S, McCarthy M, Collins A, McCafferty C, McAuliffe F. Exploring engagement with health apps: the emerging importance of situational involvement and individual characteristics. European Journal of Marketing 2021;55(13):122 View
  5. Rivera-Romero O, Gabarron E, Ropero J, Denecke K. Designing personalised mHealth solutions: An overview. Journal of Biomedical Informatics 2023;146:104500 View
  6. Taherdoost H. Deep Learning and Neural Networks: Decision-Making Implications. Symmetry 2023;15(9):1723 View
  7. Budiningsari D, Syahrian F. Validity of a digital photo-based dietary assessment tool: Development and initial evaluation. Nutrition and Health 2024 View

Books/Policy Documents

  1. Edilson U. Environmental Science and Technology: Sustainable Development II. View
  2. Mena B, Sîrbu A, Eze C. Consumer Perceptions and Food. View