A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Kiranjit Atwal
This paper provides a brief overview of AI applications in clinical nutrition and dietetics, highlighting opportunities and risks, and emphasizes the need for standardized protocols and human oversight.
Pierre Singer, Eyal Robinson, Orit Raphaeli
This review describes how AI tools, including deep learning and machine learning, can enhance clinical nutrition through improved screening, assessment, and prediction of outcomes, while addressing ethical considerations.
Tagne Poupi Theodore Armand, Kintoh Allen Nfor, Jung-In Kim, et al.
This systematic review comprehensively maps AI, ML, and DL applications in nutrition, highlighting smart personalized nutrition, dietary assessment, food recognition, and predictive modeling for disease prevention and diagnosis.
Andrea Sosa-Holwerda, Oak-Hee Park, Kembra Albracht-Schulte, et al.
This scoping review examines AI's role in nutrition research, finding it is at a developmental stage focused mainly on dietary assessment, with unresolved ethical concerns.