AI-based digital image dietary assessment methods compared to humans and ground truth: a systematic review

AI-based digital image dietary assessment methods compared to humans and ground truth: a systematic review

AbstractObjective Human error estimating food intake is a major source of bias in nutrition research. Artificial intelligence (AI) methods may reduce bias, but the overall accuracy of AI estimates is unknown. This study was a systematic review of peer-reviewed journal articles comparing fully automa...

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Bibliographic Details
Main Authors:	Eleanor Shonkoff, Kelly Copeland Cara, Xuechen (Anna) Pei, Mei Chung, Shreyas Kamath, Karen Panetta, Erin Hennessy
Format:	Article
Language:	English
Published:	Taylor & Francis Group 2023-12-01
Series:	Annals of Medicine
Subjects:	Artificial intelligence machine learning nutrition assessment nutrition surveys food images
Online Access:	https://www.tandfonline.com/doi/10.1080/07853890.2023.2273497

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