Sports nutrition as an example of effective implementation of innovative trends in nutrition: personalization and digitalization (literature review)

The nutritional status in an athlete depends on the individual genetic characteristics of the body, the level of physical and psycho-emotional stress, and a balanced diet with the inclusion of specialized food products and dietary supplements. The development of big data analytics and artificial intelligence can contribute to the development of nutritional recommendations at the individual or stratified level. The purpose of the review is to analyze and summarize research papers devoted to the possibilities of using digital technologies, deep machine learning techniques, and artificial intelligence in the field of sports nutrition to ensure a personalized approach to improving professional success. There were studied papers published in 2004–2024 in domestic and foreign electronic databases: Web of Science, Scopus, eLIBRARY.RU, Russian State Library, library collection of the Federal State Budgetary Scientific Institution “Federal Research Center of Nutrition and Biotechnology”. The potential for AI-based technologies in sports nutrition is extremely diverse: dietary assessment, recognition and tracking of food diversity, predictive modelling of athletic performance and non-communicable diseases, and selection of personalized diets. To ensure sustainable growth in the coverage of digital products and technologies, further directions for their application in sports medicine should be aimed at improving the quality and standardization of data and reducing algorithmic bias.