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@article{209156,
        author = {Amu Lawrence Chukwuemeka and Igboke Sunday Onwe},
        title = {The Role of Artificial Intelligence in Nutritional Biochemistry: A Review},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {5},
        pages = {894-901},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=209156},
        abstract = {Artificial Intelligence (AI), encompassing Machine Learning (ML) and Deep Learning (DL), is reshaping nutritional biochemistry and accelerating the transition from generalized dietary guidelines toward Precision Nutrition. The objective of this review was to synthesize current evidence on AI applications across the nutritional biochemistry pipeline, from dietary assessment to personalized intervention. 
Literature published between 2015 and 2026 was retrieved from PubMed, Scopus, ScienceDirect, and Google Scholar using combinations of search terms relating to AI, machine learning, nutritional biochemistry, metabolomics, nutrigenomics, and the gut microbiome. The evidence shows that Computer Vision models, including Convolutional Neural Networks, now enable objective food recognition and portion estimation with volume errors as low as 10.5%, while Natural Language Processing and Large Language Models standardize unstructured dietary text with dietitian-level accuracy. ML algorithms support dynamic nutrient estimation beyond static food composition tables, discover dietary and disease biomarkers across metabolomics, lipidomics, and proteomics, and integrate multi-omics data to decipher gene–diet and diet–microbiome interactions, enabling metabotyping, prediction of individual nutrient requirements, and the design of personalized functional foods and probiotics. Significant challenges remain, including data privacy, algorithmic bias, limited model explainability, and inadequate representation of diverse populations, particularly in low-resource settings. We conclude that AI provides the computational foundation for individualized, biochemically informed dietary strategies capable of preventing and managing chronic diseases, provided that ethical, regulatory, and validation frameworks mature alongside the technology.},
        keywords = {Artificial Intelligence; Nutritional Biochemistry; Precision Nutrition; Machine Learning; Metabolomics; Gut Microbiome},
        month = {October},
        }