Translational Algorithms for Technological Dietary Quality Assessment Integrating Nutrimetabolic Data with Machine Learning Methods DOI Open Access
Víctor de la O, Edwin Fernández‐Cruz, Pilar Matía‐Martín

и другие.

Nutrients, Год журнала: 2024, Номер 16(22), С. 3817 - 3817

Опубликована: Ноя. 7, 2024

Recent advances in machine learning technologies and omics methodologies are revolutionizing dietary assessment by integrating phenotypical, clinical, metabolic biomarkers, which crucial for personalized precision nutrition. This investigation aims to evaluate the feasibility efficacy of artificial intelligence tools, particularly (ML) methods, analyzing these biomarkers characterize food nutrient intake predict patterns.

Язык: Английский

Advances in Food-as-Medicine interventions and their impact on future food production, processing, and supply chains DOI Creative Commons
Thijs Defraeye, Flora Bahrami, Tobias Kowatsch

и другие.

Advances in Nutrition, Год журнала: 2025, Номер unknown, С. 100421 - 100421

Опубликована: Апрель 1, 2025

Food-as-Medicine (FAM) is an emerging trend among medical doctors, health insurers, startups, and governmental public-health non-governmental organizations. FAM implies using food as a part of individual's plan to prevent or help treat acute chronic conditions diseases. We highlight trends hurdles in the intervention pyramid. Our viewpoint indicate how interventions might change future demand for specific groups, their transport supply chains, technologies used process them. Based on national guidelines, dietary can many diseases, including cardiovascular disease, cancers, type 2 diabetes, obesity. R&D services offer more individualized treatments. This challenging given inter-individual variability complexity body's response related factors, such habits, genetics, lifestyle, biosphere. Quantifying improvements essential prove added value compared adopting general healthy diet. It unclear which level individualization produces largest benefits at lowest costs patient, healthcare system, climate. support complement conventional treatment. They will require shift producing health-promoting foods, whole minimally-processed selected processed foods. The processing industry chains must adapt these new scenarios. Auxiliary methods are enablers, delivery services, wearable technology, health-monitoring apps, data-driven consumer behavior analysis.

Язык: Английский

Процитировано

0

Translational Algorithms for Technological Dietary Quality Assessment Integrating Nutrimetabolic Data with Machine Learning Methods DOI Open Access
Víctor de la O, Edwin Fernández‐Cruz, Pilar Matía‐Martín

и другие.

Nutrients, Год журнала: 2024, Номер 16(22), С. 3817 - 3817

Опубликована: Ноя. 7, 2024

Recent advances in machine learning technologies and omics methodologies are revolutionizing dietary assessment by integrating phenotypical, clinical, metabolic biomarkers, which crucial for personalized precision nutrition. This investigation aims to evaluate the feasibility efficacy of artificial intelligence tools, particularly (ML) methods, analyzing these biomarkers characterize food nutrient intake predict patterns.

Язык: Английский

Процитировано

1