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

Mobile Health (mhealth) (2941) Artificial Intelligence (1371) Food Sciences and Nutrition Engineering (54) Innovations and Technology for Healthy Eating Education (414) Instruments and Questionnaires for Nutrition and Food Intake (166)

Published on in Vol 24, No 11 (2022): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40449, first published .
Relative Validation of an Artificial Intelligence–Enhanced, Image-Assisted Mobile App for Dietary Assessment in Adults: Randomized Crossover Study

Relative Validation of an Artificial Intelligence–Enhanced, Image-Assisted Mobile App for Dietary Assessment in Adults: Randomized Crossover Study

Relative Validation of an Artificial Intelligence–Enhanced, Image-Assisted Mobile App for Dietary Assessment in Adults: Randomized Crossover Study

Authors of this article:

Audrey Moyen1, 2 Author Orcid Image ;   Aviva Ilysse Rappaport1 Author Orcid Image ;   Chloé Fleurent-Grégoire1, 2 Author Orcid Image ;   Anne-Julie Tessier1, 2 Author Orcid Image ;   Anne-Sophie Brazeau1 Author Orcid Image ;   Stéphanie Chevalier1, 2, 3 Author Orcid Image
Article Authors Cited by (11) Tweetations (12) Metrics

Journals

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  7. Atwal K. Artificial intelligence in clinical nutrition and dietetics: A brief overview of current evidence. Nutrition in Clinical Practice 2024;39(4):736 View
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  10. Ho D, Chiu W, Kao J, Tseng H, Lin C, Huang P, Fang Y, Chen K, Su T, Yang C, Yao C, Su H, Wei P, Chang J. Reliability Issues of Mobile Nutrition Apps for Cardiovascular Disease Prevention: Comparative Study. JMIR mHealth and uHealth 2024;12:e54509 View