Artificial Intelligence Applications to Measure Food and Nutrient Intakes: Scoping Review.

Journal: Journal of medical Internet research
PMID: 39608003

Abstract

BACKGROUND: Accurate measurement of food and nutrient intake is crucial for nutrition research, dietary surveillance, and disease management, but traditional methods such as 24-hour dietary recalls, food diaries, and food frequency questionnaires are often prone to recall error and social desirability bias, limiting their reliability. With the advancement of artificial intelligence (AI), there is potential to overcome these limitations through automated, objective, and scalable dietary assessment techniques. However, the effectiveness and challenges of AI applications in this domain remain inadequately explored.

Authors

  • Jiakun Zheng
    School of Economics and Management, Shanghai University of Sport, Shanghai, China.
  • Junjie Wang
    School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China.
  • Jing Shen
    Department of Physical Education, China University of Geosciences, Beijing, China.
  • Ruopeng An
    Silver School of Social Work, New York University, New York, NY, 10012, USA. Electronic address: ra4605@nyu.edu.

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