AI Applications for Nutrition and Food Security Research

Abstract

Data analytics (DA) and artificial intelligence (AI) play increasingly vital roles in food, nutrition, environment, and public health research and practice. With the continued successful development, professionals in these fields could rely on data analytics and AI for tasks such as data collection, decision-making, and policy development. Proficiency in research methods, statistical analysis, and ethical considerations is crucial. As AI applications grow in complexity, it is essential for professionals and the public to embrace and regulate them effectively. This review outlines AI’s diverse applications in nutrition research, including data analysis, prediction, personalized recommendations, and food safety monitoring. Select illustrative examples demonstrate its potential across various domains and highlight common challenges. The narrative underscores the importance of integrating data science and AI competencies into graduate education to equip the modern workforce.