Artificial Intelligence is playing an increasingly important role in advancing Nutritional Studies by providing innovative solutions to complex research challenges. The role of artificial intelligence in nutritional studies enables the processing and analysis of large datasets, allowing for more accurate modeling of how nutrients affect metabolism and disease progression. In nutritional epidemiology, AI helps identify trends in diet patterns and their associations with chronic diseases. Furthermore, AI-powered technologies like predictive analytics can assist in creating personalized dietary interventions that optimize health based on individual profiles, such as genetics, lifestyle, and health history. As AI continues to evolve, it is poised to revolutionize nutritional science, offering precise and data-driven approaches to improving global health outcomes and combating nutrition-related diseases.
Title : The software tools for FOP nutrition labelling
Vintila luliana, University ”Dunarea de Jos” Galati, Romania
Title : Translation modulators to preserve neurodegenerative decline from metal toxicity
Jack Timothy Rogers, Harvard University, United States
Title : Farmers’ food literacy: A scoping review
Sarah Hennessy, Atlantic Technological University, Ireland
Title : Nutrients and bioactive compounds of non-traditional green leafy vegetables: A natural path to better health
Safiullah Pathan, Lincoln University of Missouri, United States
Title : AI-powered nutrition strategies for critically ill patients: Transforming outcomes in the ICU
Ali Amirsavadkouhi, Arta Arti Health Innovation, United Arab Emirates
Title : Where west meets east? Time to globalise Traditional, Complementary and Integrative Medicine (TCIM)
Dilip Ghosh, Nutriconnect, Australia