Diet & Nutrition

Learning machine approach reveals microbial signatures of diet and sex in dog.

The characterization of the microbial population of many niches of the organism, as the gastrointestinal tract, is now possible thanks to the use of high-throughput DNA sequencing technique. Several studies in the companion animals field already investigated faecal microbiome in healthy or affected subjects, although the methodologies used in the different laboratories and the limited number of an...

Machine Learning Models to Predict Childhood and Adolescent Obesity: A Review.

The prevalence of childhood and adolescence overweight an obesity is raising at an alarming rate in many countries. This poses a serious threat to the current and near-future health systems, given the association of these conditions with different comorbidities (cardiovascular diseases, type II diabetes, and metabolic syndrome) and even death. In order to design appropriate strategies for its prev...

Deep learning method for localization and segmentation of abdominal CT.

Computed Tomography (CT) imaging is widely used for studying body composition, i.e., the proportion of muscle and fat tissues with applications in are...

Machine Learning based histology phenotyping to investigate the epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits.

Genetic studies have recently highlighted the importance of fat distribution, as well as overall adiposity, in the pathogenesis of obesity-associated ...

A machine learning-based approach for estimating and testing associations with multivariate outcomes.

We propose a method for summarizing the strength of association between a set of variables and a multivariate outcome. Classical summary measures are ...

The association between vitamin D level and periodontal disease in Saudi population, a preliminary study.

OBJECTIVE: Among other regulatory functions, vitamin D has a role in modulating the inflammatory process of periodontal disease. Therefore, this retro...

Geographic origin discrimination of pork from different Chinese regions using mineral elements analysis assisted by machine learning techniques.

Porkis thelargest-producedandmost-consumedmeat intheworld, and the food market globalization has increased public attention to food origin. Therefore,...

goFOOD: An Artificial Intelligence System for Dietary Assessment.

Accurate estimation of nutritional information may lead to healthier diets and better clinical outcomes. We propose a dietary assessment system based ...

Deep learning of lumbar spine X-ray for osteopenia and osteoporosis screening: A multicenter retrospective cohort study.

Osteoporosis is a prevalent but underdiagnosed condition. As compared to dual-energy X-ray absorptiometry (DXA) measures, we aimed to develop a deep c...

Identification of predictive factors of the degree of adherence to the Mediterranean diet through machine-learning techniques.

Food consumption patterns have undergone changes that in recent years have resulted in serious health problems. Studies based on the evaluation of the...

Integration of an interpretable machine learning algorithm to identify early life risk factors of childhood obesity among preterm infants: a prospective birth cohort.

BACKGROUND: The early life risk factors of childhood obesity among preterm infants are unclear and little is known about the influence of the feeding ...

A Physical Activity and Diet Program Delivered by Artificially Intelligent Virtual Health Coach: Proof-of-Concept Study.

BACKGROUND: Poor diet and physical inactivity are leading modifiable causes of death and disease. Advances in artificial intelligence technology prese...

Stability assessment of extracts obtained from Arbutus unedo L. fruits in powder and solution systems using machine-learning methodologies.

Arbutus unedo L. (strawberry tree) has showed considerable content in phenolic compounds, especially flavan-3-ols (catechin, gallocatechin, among othe...

An artificial neural network approach for predicting hypertension using NHANES data.

This paper focus on a neural network classification model to estimate the association among gender, race, BMI, age, smoking, kidney disease and diabet...

Age-related Macular Degeneration: Nutrition, Genes and Deep Learning-The LXXVI Edward Jackson Memorial Lecture.

PURPOSE: To evaluate the importance of nutritional supplements, dietary pattern, and genetic associations in age-related macular degeneration (AMD); a...

Technological and antioxidant properties of proteins obtained from waste potato juice.

The article presents the technological and antioxidant properties of potato juice (PJ) protein concentrate obtained by the novel ultrafiltration metho...

Safety and efficacy of subcutaneous alpha-tocopherol in healthy adult horses.

Vitamin E is essential for neuromuscular function. The primary treatment, oral supplementation with natural ('RRR') α-tocopherol, is not effective in ...

Machine-learning based exploration of determinants of gray matter volume in the KORA-MRI study.

To identify the most important factors that impact brain volume, while accounting for potential collinearity, we used a data-driven machine-learning a...

Prediction of the Influential Factors on Eating Behaviors: A Hybrid Model of Structural Equation Modelling-Artificial Neural Networks.

The importance of eating behavior risk factors in the primary prevention of obesity has been established. Researchers mostly use the linear model to d...

Evolution of renal function in patients with severe intestinal failure on home parenteral nutrition.

BACKGROUND: Kidney disease is a frequent but underestimated complication in patients suffering from intestinal failure (IF) treated by long-term home ...