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Critical Reviews in Food Science and Nutrition Volume 63, 2023 - Issue 7
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Applicability of machine learning techniques in food intake assessment: A systematic review

Larissa Oliveira Chavesa Department of Nutrition and Health, Universidade Federal de Viçosa, Viçosa, BrazilCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-6962-2284View further author information
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Ana Luiza Gomes Domingosa Department of Nutrition and Health, Universidade Federal de Viçosa, Viçosa, BrazilORCID Iconhttps://orcid.org/0000-0001-7010-0574View further author information
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Daniel Louzada Fernandesb Department of Informatics, Universidade Federal de Viçosa, Viçosa, BrazilORCID Iconhttps://orcid.org/0000-0002-6548-294XView further author information
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Fabio Ribeiro Cerqueirac Department of Production Engineering, Universidade Federal Fluminense, Petrópolis, BrazilORCID Iconhttps://orcid.org/0000-0003-1325-2592View further author information
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Rodrigo Siqueira-Batistad Department of Medicine and Nursing, Universidade Federal de Viçosa, Viçosa, Brazil;e School of Medicine of the Faculdade Dinâmica do Vale do Piranga, Ponte Nova, BrazilORCID Iconhttps://orcid.org/0000-0002-3661-1570View further author information
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Josefina Bressana Department of Nutrition and Health, Universidade Federal de Viçosa, Viçosa, BrazilORCID Iconhttps://orcid.org/0000-0002-4993-9436View further author information
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Pages 902-919 | Published online: 29 Jul 2021

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Eleanor Shonkoff, Kelly Copeland Cara, Xuechen (Anna) Pei, Mei Chung, Shreyas Kamath, Karen Panetta & Erin Hennessy. (2023) AI-based digital image dietary assessment methods compared to humans and ground truth: a systematic review. Annals of Medicine 55:2.
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Articles from other publishers (5)

Chigoziem Andrew Iheanacho & Olufunke Rebecca Vincent. (2022) Classification and recommendation of food intake in West Africa for healthy diet using Deep Learning. Classification and recommendation of food intake in West Africa for healthy diet using Deep Learning.
Radwan Qasrawi, Stephanny Paola Vicuna Polo, Diala Abu Al-Halawa, Sameh Hallaq & Ziad Abdeen. (2022) Assessment and Prediction of Depression and Anxiety Risk Factors in Schoolchildren: Machine Learning Techniques Performance Analysis. JMIR Formative Research 6:8, pages e32736.
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Hanne Pedersen, Lars Jorge Diaz, Kim Katrine Bjerring Clemmensen, Marie Mølle Jensen, Marit Eika Jørgensen, Graham Finlayson, Jonas Salling Quist, Dorte Vistisen & Kristine Færch. (2022) Predicting Food Intake from Food Reward and Biometric Responses to Food Cues in Adults with Normal Weight Using Machine Learning. The Journal of Nutrition 152:6, pages 1574-1581.
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Radwan Qasrawi & Diala Abu Al-Halawa. (2022) Cluster Analysis and Classification Model of Nutritional Anemia Associated Risk Factors Among Palestinian Schoolchildren, 2014. Frontiers in Nutrition 9.
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Weiqing Min, Chunlin Liu, Leyi Xu & Shuqiang Jiang. (2022) Applications of knowledge graphs for food science and industry. Patterns 3:5, pages 100484.
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