Advancements in Using AI for Dietary Assessment Based on Food Images: Scoping Review.

ABSTRACT:

Background

To accurately capture an individual's food intake, dietitians are often required to ask clients about their food frequencies and portions, and they have to rely on the client's memory, which can be burdensome. While taking food photos alongside food records can alleviate user burden and reduce errors in self-reporting, this method still requires trained staff to translate food photos into dietary intake data. Image-assisted dietary assessment (IADA) is an innovative approach that uses computer algorithms to mimic human performance in estimating dietary information from food images. This field has seen continuous improvement through advancements in computer science, particularly in artificial intelligence (AI). However, the technical nature of this field can make it chall

SUBMITTER: Chotwanvirat P 

PROVIDER: S-EPMC11607557 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature