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The aim of this article is to address the current state of AI in nutrition and metabolic liver disease and to understand how AI can be utilized to address gaps in the care of patients with liver disease, particularly as it relates to their nutrition.
28 Ιουν 2024 · This review’s purpose is four-fold: (i) to investigate AI’s role in nutrition research; (ii) to identify areas in nutrition using AI; (iii) to understand AI’s future potential impact; (iv) to investigate possible concerns about AI’s use in nutrition research.
30 Ιουν 2023 · AI can help formulate individualized nutrition diet plans. A personalized approach implies that differences between individuals in biochemical, metabolic, and genetic factors, as well as gut bacteria, may explain different phenotypic changes to specific interventions [ 26 ].
15 Σεπ 2021 · AI algorithms may help better understand and predict the complex and non-linear interactions between nutrition-related data and health outcomes, particularly when large amounts of data need to be structured and integrated, such as in metabolomics.
Artificial Intelligence (AI) has the potential to dramatically change the field of healthcare and nutrition by imitating human cognitive processes. This field involves smart machine-based applications, such as Machine Learning (ML), neural networks, and natural language processing to tackle and solve various issues.
17 Απρ 2023 · Download PDF. Summary. Artificial Intelligence (AI) is a rapidly emerging technology in healthcare that has the potential to revolutionise clinical nutrition. AI can assist in analysing complex data, interpreting medical images, and providing personalised nutrition interventions for patients.
22 Ιαν 2021 · The review of the publications revealed three application areas of AI technology: biomedical nutrients research, clinical nutrients research and nutritional epidemiology.
