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

Journal: Journal of medical Internet research
PMID:

Abstract

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-assisted food diary that integrates artificial intelligence food recognition. We hypothesized that Keenoa is as valid for dietary assessment as the automated self-administered 24-hour recall (ASA24)-Canada and better appreciated by users.

Authors

  • Audrey Moyen
    School of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, QC, Canada.
  • Aviva Ilysse Rappaport
    School of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, QC, Canada.
  • Chloé Fleurent-Grégoire
    School of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, QC, Canada.
  • Anne-Julie Tessier
    School of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, QC, Canada.
  • Anne-Sophie Brazeau
    School of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, QC, Canada.
  • Stéphanie Chevalier
    School of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, QC, Canada.