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

BACKGROUND: Thorough dietary assessment is essential to obtain accurate food and nutrient intake data yet challenging because of the limitations of current methods. Image-based methods may decrease energy underreporting and increase the validity of self-reported dietary intake. Keenoa is an image-as...

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Detalles Bibliográficos
Autores principales: Moyen, Audrey, Rappaport, Aviva Ilysse, Fleurent-Grégoire, Chloé, Tessier, Anne-Julie, Brazeau, Anne-Sophie, Chevalier, Stéphanie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9723975/
https://www.ncbi.nlm.nih.gov/pubmed/36409539
http://dx.doi.org/10.2196/40449

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9723975/
https://www.ncbi.nlm.nih.gov/pubmed/36409539
http://dx.doi.org/10.2196/40449

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