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

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.

Objective

This study aimed to conduct a scoping review to synthesize existing literature on the efficacy, accuracy, and challenges of using AI tools in assessing food

SUBMITTER: Zheng J 

PROVIDER: S-EPMC11638690 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature