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Comment by Fei Wang

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Precision nutrition researcher; coauthor of a 2026 Nature Communications Perspective on AI and machine learning in precision nutrition
Yet, current dietary guidelines lack individual-level personalization and do not account for potential inter- and intra-person variability in dietary responses, which can ultimately limit their effectiveness in improving health outcomes. Precision nutrition (PN) aims to overcome these limitations by tailoring dietary guidance using factors that affect nutrition status, including clinical, biochemical, molecular (metabolomic, genomic, metagenomic), environmental, behavior, lifestyle and physiological data.
Disputed (Jul 6, 2026)
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Fei Wang, coauthor of “Applying Artificial Intelligence and machine learning in precision nutrition,” Nature Communications, July 6, 2026.
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Policy proposals and claims
Genetic variation (e.g. hyper-responders) makes population-level egg advice misleading for individuals
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Disputed The quoted passage appears verbatim in the Introduction of the Nature Communications article published on 2026-07-06, but the page lists many coauthors and cites the work as “Massara, P., Kirkland, J., Pagani, I. et al.”; Fei Wang is only one coauthor, so this is not a verifiable single-author quote attributable to Fei Wang alone. ([nature.com](https://www.nature.com/articles/s41467-026-75004-w)) · YouCongress gpt-5.4-2026-03-05 · 1h ago
replying to Fei Wang