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Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45332, first published .
Predicting Unreported Micronutrients From Food Labels: Machine Learning Approach

Predicting Unreported Micronutrients From Food Labels: Machine Learning Approach

Predicting Unreported Micronutrients From Food Labels: Machine Learning Approach

Authors of this article:

Rouzbeh Razavi1 Author Orcid Image ;   Guisen Xue1 Author Orcid Image

Journals

  1. Priya K, Alur S. Benchmarking nutrition facts panel label – a consumer ethics perspective using health belief model. Benchmarking: An International Journal 2025;32(4):1434 View
  2. K M P, Babu K, S S. Discovering Consumer Behavior Towards Back-of-Pack Nutrition Labels: A Systematic Literature Review. Current Research in Nutrition and Food Science Journal 2024;12(2):502 View
  3. Dar B. Cereal brans: Transforming upcycled ingredients for sustainable food solutions aligned with SDGs. Trends in Food Science & Technology 2024;153:104738 View
  4. Yu B, Liu S. Deep learning application for marketing engagement – its thematic evolution. Journal of Research in Interactive Marketing 2025;19(5):861 View
  5. Yang X, Ho C, Gao X, Chen N, Chen F, Zhu Y, Zhang X. Machine learning: An effective tool for monitoring and ensuring food safety, quality, and nutrition. Food Chemistry 2025;477:143391 View
  6. Akpojevwe Abafe E, Smith N, Maxwell T, McNabb W. Trends in micronutrient research since the SDGs: a global perspective. Critical Reviews in Food Science and Nutrition 2025;65(31):7871 View
  7. Yin B, Tan G, Muhammad R, Liu J, Bi J. AI-Powered Innovations in Food Safety from Farm to Fork. Foods 2025;14(11):1973 View
  8. Revesai Z, Kogeda O. Lightweight Interpretable Deep Learning Model for Nutrient Analysis in Mobile Health Applications. Digital 2025;5(2):23 View
  9. Revesai Z, Kogeda O. Self-Explaining Neural Networks for Food Recognition and Dietary Analysis. BioMedInformatics 2025;5(3):36 View
  10. Ghazal P, Waheed M, Muneer S. Utilization of nutritional food label for management of non-communicable diseases among Pakistani population. International Journal of Health Promotion and Education 2025:1 View
  11. Pratas C, Ramos F, Arrais J, Silva A. Review of advanced algorithms and imaging techniques in food analysis: a path to the future. Trends in Food Science & Technology 2026;168:105504 View
  12. Quan W, Zhou J, Wang J, Huang J, Du L. Machine Learning-Driven Precision Nutrition: A Paradigm Evolution in Dietary Assessment and Intervention. Nutrients 2025;18(1):45 View
  13. Adil M, Fan Y, Xiao X, Zou Y, Ren J, Faisal Manzoor M. Artificial Intelligence and Machine Learning: Shaping the Future of Food Safety, Quality Control, Traceability Systems, and Nutrition. Food Reviews International 2026:1 View
  14. Feng J, Zheng F, Zhang Y, Zeng X, Wang Z, Liang J, Wang Z, Ji L, Shen Q. Exploring the broad spectrum of machine learning technologies in the food sector: A comprehensive review of techniques and practical applications. Current Research in Food Science 2026;12:101406 View

Conference Proceedings

  1. Bora K. 2025 IEEE International Conference on Big Data (BigData). NutriLite: Balancing Accuracy and Efficiency in Food Nutrient Estimation with Small Language Models View