Diet & Nutrition

Environmental contaminants in coastal populations: Comparisons with the National Health and Nutrition Examination Survey (NHANES) and resident dolphins.

BACKGROUND: People living in coastal communities are at risk for exposure to environmental hazards, including legacy chemicals. We can use databases such as NHANES to assess whether contaminants in coastal communities are present in higher levels than in the United States overall. We can use information from studies of local animal populations to assess which of these contaminants could have been ...

Artificial Intelligence in Musculoskeletal Imaging: A Paradigm Shift.

Artificial intelligence is upending many of our assumptions about the ability of computers to detect and diagnose diseases on medical images. Deep learning, a recent innovation in artificial intelligence, has shown the ability to interpret medical images with sensitivities and specificities at or near that of skilled clinicians for some applications. In this review, we summarize the history of art...

Laser-based classification of olive oils assisted by machine learning.

Olive oil is an essential diet component in all Mediterranean countries having a considerable impact on the local economies, which are producing almos...

Safety of viable embryonated eggs of the whipworm as a novel food pursuant to Regulation (EU) 2015/2283.

Following a request from the European Commission, the EFSA Panel on Nutrition, Novel Foods and Food Allergens (NDA) was asked to deliver an opinion on...

Comparisons among Machine Learning Models for the Prediction of Hypercholestrolemia Associated with Exposure to Lead, Mercury, and Cadmium.

Lead, mercury, and cadmium are common environmental pollutants in industrialized countries, but their combined impact on hypercholesterolemia (HC) is ...

Phenotyping Women Based on Dietary Macronutrients, Physical Activity, and Body Weight Using Machine Learning Tools.

Nutritional phenotyping can help achieve personalized nutrition, and machine learning tools may offer novel means to achieve phenotyping. The primary ...

Demographic, psychological, behavioral, and cognitive correlates of BMI in youth: Findings from the Adolescent Brain Cognitive Development (ABCD) study.

BACKGROUND: Previous research has implicated demographic, psychological, behavioral, and cognitive variables in the onset and maintenance of pediatric...

Raman spectroscopic histology using machine learning for nonalcoholic fatty liver disease.

Histopathology requires the expertise of specialists to diagnose morphological features of cells and tissues. Raman imaging can provide additional bio...

Impact of lunch provision on anthropometry, hemoglobin, and micronutrient status of female Cambodian garment workers: exploratory randomized controlled trial.

BACKGROUND: Lunch provision is expected to improve the nutritional status of Cambodian garment workers. The objective of this study is to evaluate the...

Identifying depression in the National Health and Nutrition Examination Survey data using a deep learning algorithm.

BACKGROUND: As depression is the leading cause of disability worldwide, large-scale surveys have been conducted to establish the occurrence and risk f...

HyperFoods: Machine intelligent mapping of cancer-beating molecules in foods.

Recent data indicate that up-to 30-40% of cancers can be prevented by dietary and lifestyle measures alone. Herein, we introduce a unique network-base...

Changes in clinical indicators related to the transition from dialysis to kidney transplantation-data from the ERA-EDTA Registry.

BACKGROUND: Kidney transplantation should improve abnormalities that are common during dialysis treatment, like anaemia and mineral and bone disorder....

Screening and Assessment of Bone Health in Indian Women Using an Indigenous ELISA of Human Osteocalcin a Bone Turnover Marker.

Osteoporosis a major public health problem of the elderly, is associated with substantial morbidity and socio economic burden. The aim of the study wa...

An Ontology to Standardize Research Output of Nutritional Epidemiology: From Paper-Based Standards to Linked Content.

BACKGROUND: The use of linked data in the Semantic Web is a promising approach to add value to nutrition research. An ontology, which defines the logi...

Promising Artificial Intelligence-Machine Learning-Deep Learning Algorithms in Ophthalmology.

The lifestyle of modern society has changed significantly with the emergence of artificial intelligence (AI), machine learning (ML), and deep learning...

Non-Invasive Sensing of Nitrogen in Plant Using Digital Images and Machine Learning for ssp. L.

Monitoring plant nitrogen (N) in a timely way and accurately is critical for precision fertilization. The imaging technology based on visible light is...

Instant White Rice with Pigmented Giant Embryonic Rice Improves Glucose Metabolism and Inhibits Oxidative Stress in High-Fat Diet-Fed Mice.

The effects of instant cooked rice made from a combination of white rice and pigmented giant embryonic Keunnunjami rice, in comparison with those of i...

Predicting nationwide obesity from food sales using machine learning.

The obesity epidemic progresses everywhere across the globe, and implementing frequent nationwide surveys to measure the percentage of obese populatio...

Effects of obesity on breast size, thoracic spine structure and function, upper torso musculoskeletal pain and physical activity in women.

PURPOSE: This study investigated the effects of obesity on breast size, thoracic spine structure and function, upper torso musculoskeletal pain and ph...

Directional Relationship Between Vitamin D Status and Prediabetes: A New Approach from Artificial Neural Network in a Cohort of Workers with Overweight-Obesity.

Despite the increasing literature on the association of diabetes with inflammation, cardiovascular risk, and vitamin D (25(OH)D) concentrations, stro...