Chapter 13: Precision Nutrition in the Age of AI: An Immersive Wellness Approach to Dietary Care

Machine learning (ML) is a valuable tool for analysing data in nutrition, particularly in areas of metabolic disorders. However, nutrition experts often lack an understanding of ML, which limits its potential to address open questions. This chapter explores the role of ML in the nutrition care process (NCP) and clinical research. It highlights the importance of ML in analysing complex data, particularly in metabolic disorders. ML can improve diet assessments and personalised plans, and manage health conditions. Artificial intelligence (AI) technologies enhance dietary tracking accuracy, reduce errors, and improve nutrient content analysis. Collaboration among industry experts, healthcare professionals, researchers, and policymakers is needed for the future impact of ML on nutrition science. ML algorithms are powerful for studying metabolic disorders and integrating multiple data types to inform predictive models. However, ML faces practical limitations, such as substantial data collection, hardware, and infrastructure expenses. Despite these challenges, ML can mitigate the burden of nutrition-related ill health in society. This chapter concludes that ML can significantly help nutritionists, medical professionals, and healthcare stakeholders in the NCP process, with future scope for using ML in community nutrition research and precision nutrition.