AIMC Topic: Diet
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Suitability of different machine learning algorithms for the classification of the proportion of grassland-based forages at the herd level using mid-infrared spectral information from routine milk control.
Journal of dairy science
Aug 30, 2024
As the call for an international standard for milk from grassland-based production systems continues to grow, so too do the monitoring and evaluation policies surrounding this topic. Individual stipulations by countries and milk producers to market t...
Pseudo-random Number Generator Influences on Average Treatment Effect Estimates Obtained with Machine Learning.
Epidemiology (Cambridge, Mass.)
Aug 16, 2024
BACKGROUND: The use of machine learning to estimate exposure effects introduces a dependence between the results of an empirical study and the value of the seed used to fix the pseudo-random number generator.
Artificial Intelligence and Health Inequities in Dietary Interventions on Atherosclerosis: A Narrative Review.
Nutrients
Aug 7, 2024
Poor diet is the top modifiable mortality risk factor globally, accounting for 11 million deaths annually with half being from diet-linked atherosclerotic cardiovascular disease (ASCVD). Yet, most of the world cannot afford a healthy diet-as the hidd...
Evaluating the Quality and Comparative Validity of Manual Food Logging and Artificial Intelligence-Enabled Food Image Recognition in Apps for Nutrition Care.
Nutrients
Aug 5, 2024
For artificial intelligence (AI) to support nutrition care, high quality and accuracy of its features within smartphone applications (apps) are essential. This study evaluated popular apps' features, quality, behaviour change potential, and comparati...
Optimizing postprandial glucose prediction through integration of diet and exercise: Leveraging transfer learning with imbalanced patient data.
PloS one
Aug 1, 2024
BACKGROUND: In recent years, numerous methods have been introduced to predict glucose levels using machine-learning techniques on patients' daily behavioral and continuous glucose data. Nevertheless, a definitive consensus remains elusive regarding m...
Machine learning uncovers manganese as a key nutrient associated with reduced risk of steatotic liver disease.
Liver international : official journal of the International Association for the Study of the Liver
Jul 31, 2024
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects approximately 20%-30% of the general population and is linked to high-caloric western style diet. However, there are little data that specific nutrients might help t...
Evaluation of online chat-based artificial intelligence responses about inflammatory bowel disease and diet.
European journal of gastroenterology & hepatology
Jul 8, 2024
INTRODUCTION: The USA has the highest age-standardized prevalence of inflammatory bowel disease (IBD). Both genetic and environmental factors have been implicated in IBD flares and multiple strategies are centered around avoiding dietary triggers to ...
Relationships between minerals' intake and blood homocysteine levels based on three machine learning methods: a large cross-sectional study.
Nutrition & diabetes
Jun 1, 2024
BACKGROUND: Blood homocysteine (Hcy) level has become a sensitive indicator in predicting the development of cardiovascular disease. Studies have shown an association between individual mineral intake and blood Hcy levels. The effect of mixed mineral...
Machine Learning Identification of Nutrient Intake Variations across Age Groups in Metabolic Syndrome and Healthy Populations.
Nutrients
May 28, 2024
This study undertakes a comprehensive examination of the intricate link between diet nutrition, age, and metabolic syndrome (MetS), utilizing advanced artificial intelligence methodologies. Data from the National Health and Nutrition Examination Surv...
The development of an EU-wide nutrition and physical activity expert knowledge base to support a personalised mobile application across various EU population groups.
Nutrition bulletin
May 21, 2024
A healthy lifestyle comprising regular physical activity and an adequate diet is imperative for the prevention of non-communicable diseases such as hypertension and some cancers. Advances in information computer technology offer the opportunity to pr...
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