AIMC Topic: Diet

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Current Developments in Digital Quantitative Volume Estimation for the Optimisation of Dietary Assessment.

Nutrients
Obesity is a global health problem with wide-reaching economic and social implications. Nutrition surveillance systems are essential to understanding and addressing poor dietary practices. However, diets are incredibly diverse across populations and ...

Food Liking-Based Diet Quality Indexes (DQI) Generated by Conceptual and Machine Learning Explained Variability in Cardiometabolic Risk Factors in Young Adults.

Nutrients
The overall pattern of a diet (diet quality) is recognized as more important to health and chronic disease risk than single foods or food groups. Indexes of diet quality can be derived theoretically from evidence-based recommendations, empirically fr...

CHD Risk Minimization through Lifestyle Control: Machine Learning Gateway.

Scientific reports
Studies on the influence of a modern lifestyle in abetting Coronary Heart Diseases (CHD) have mostly focused on deterrent health factors, like smoking, alcohol intake, cheese consumption and average systolic blood pressure, largely disregarding the i...

Effects of post-weaning supplementation of immunomodulatory feed ingredient on body weight and cortisol concentrations in program-fed beef heifers.

Domestic animal endocrinology
The objective of this study was to determine the effects of an immunomodulatory feed ingredient during post-weaning on growth and cortisol concentrations of beef heifers. Commercial Angus heifers (n = 72) from 2 AI sires were blocked (n = 9) by BW an...

Flavonoid bioactive compounds of hawthorn extract can promote growth, regulate electrocardiogram waves, and improve cardiac parameters of pulmonary hypertensive chickens.

Poultry science
The effect of orally administered hawthorn flavonoid extract (HFE) on growth, electrocardiographic waves, and cardiac parameters of pulmonary hypertensive chickens reared at high altitude (2,100 m above sea level) was examined. A total of 225 one-day...

Nutrient Estimation from 24-Hour Food Recalls Using Machine Learning and Database Mapping: A Case Study with Lactose.

Nutrients
The Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) is a free dietary recall system that outputs fewer nutrients than the Nutrition Data System for Research (NDSR). NDSR uses the Nutrition Coordinating Center (NCC) Food and Nutrie...

Metabolomics meets machine learning: Longitudinal metabolite profiling in serum of normal versus overconditioned cows and pathway analysis.

Journal of dairy science
This study aimed to investigate the differences in the metabolic profiles in serum of dairy cows that were normal or overconditioned when dried off for elucidating the pathophysiological reasons for the increased health disturbances commonly associat...

Using machine learning to estimate herbage production and nutrient uptake on Irish dairy farms.

Journal of dairy science
Nutrient management on grazed grasslands is of critical importance to maintain productivity levels, as grass is the cheapest feed for ruminants and underpins these meat and milk production systems. Many attempts have been made to model the relationsh...

Using artificial neural networks to predict pH, ammonia, and volatile fatty acid concentrations in the rumen.

Journal of dairy science
The objectives of this study were (1) to predict ruminal pH and ruminal ammonia and volatile fatty acid (VFA) concentrations by developing artificial neural networks (ANN) using dietary nutrient compositions, dry matter intake, and body weight as inp...

Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes.

Artificial intelligence in medicine
BACKGROUND: Diabetes mellitus (DM) is a metabolic disorder that causes abnormal blood glucose (BG) regulation that might result in short and long-term health complications and even death if not properly managed. Currently, there is no cure for diabet...