Diet & Nutrition

A genome-wide association study of childhood adiposity and blood lipids.

The rising prevalence of childhood obesity and dyslipidaemia is a major public health concern due to its association with morbidity and mortality in later life. Previous studies have found that genetic variants inherited at birth can begin to exert their effects on cardiometabolic traits during the early stages of the lifecourse. In this study, we have conducted genome-wide association studies (...

Automated, calibration-free quantification of cortical bone porosity and geometry in postmenopausal osteoporosis from ultrashort echo time MRI and deep learning.

BACKGROUND: Assessment of cortical bone porosity and geometry by imaging in vivo can provide useful information about bone quality that is independent of bone mineral density (BMD). Ultrashort echo time (UTE) MRI techniques of measuring cortical bone porosity and geometry have been extensively validated in preclinical studies and have recently been shown to detect impaired bone quality in vivo in ...

2D/3D Wound Segmentation and Measurement Based on a Robot-Driven Reconstruction System.

Chronic wounds, are a worldwide health problem affecting populations and economies as a whole. With the increase in age-related diseases, obesity, and...

Machine learning models trained on synthetic datasets of multiple sample sizes for the use of predicting blood pressure from clinical data in a national dataset.

INTRODUCTION: The potential for synthetic data to act as a replacement for real data in research has attracted attention in recent months due to the p...

Robotic versus open total pancreatectomy: a systematic review and meta-analysis.

Limited data are available on postoperative outcomes in patients undergoing robotic total pancreatectomy (RTP). This systematic review and meta-analys...

Putting the Personalized Metabolic Avatar into Production: A Comparison between Deep-Learning and Statistical Models for Weight Prediction.

Nutrition is a cross-cutting sector in medicine, with a huge impact on health, from cardiovascular disease to cancer. Employment of digital medicine i...

Artificial intelligence and body composition.

AIMS: Although obesity is associated with chronic disease, a large section of the population with high BMI does not have an increased risk of metaboli...

Alternative additives associated in the feeding of laying hens: performance, biometrics, bone traits, and economic evaluation-an unsupervised machine learning approach.

Given the current bans on the use of some growth promoting antibiotics in poultry nutrition, the need to use alternative additives which could replace...

Deep-Learning for Epicardial Adipose Tissue Assessment With Computed Tomography: Implications for Cardiovascular Risk Prediction.

BACKGROUND: Epicardial adipose tissue (EAT) volume is a marker of visceral obesity that can be measured in coronary computed tomography angiograms (CC...

On stars and spikes: Resolving the skeletal morphology of planktonic Acantharia using synchrotron X-ray nanotomography and deep learning image segmentation.

Acantharia (Acantharea) are wide-spread marine protozoa, presenting one of the rare examples of strontium sulfate mineralization in the biosphere. The...

A Novel Blunge Calibration Intelligent Feature Classification Model for the Prediction of Hypothyroid Disease.

According to the Indian health line report, 12% of the population suffer from abnormal thyroid functioning. The major challenge in this disease is tha...

Age-specific risk factors for the prediction of obesity using a machine learning approach.

Machine Learning is a powerful tool to discover hidden information and relationships in various data-driven research fields. Obesity is an extremely c...

A Combined Region- and Pixel-Based Deep Learning Approach for Quantifying Abdominal Adipose Tissue in Adolescents Using Dixon Magnetic Resonance Imaging.

BACKGROUND: The development of adipose tissue during adolescence may provide valuable insights into obesity-associated diseases. We propose an automat...

Systematic Review of Machine Learning applied to the Prediction of Obesity and Overweight.

Obesity and overweight has increased in the last year and has become a pandemic disease, the result of sedentary lifestyles and unhealthy diets rich i...

Implementing machine learning methods with complex survey data: Lessons learned on the impacts of accounting sampling weights in gradient boosting.

Despite the prominent use of complex survey data and the growing popularity of machine learning methods in epidemiologic research, few machine learnin...

Lorcaserin and phentermine exert anti-obesity effects with modulation of the gut microbiota.

Although drugs have been reported to modulate the gut microbiota, the effects of anti-obesity drugs on the gut microbiota remain unclear. Lorcaserin (...

Mid-level data fusion of Raman spectroscopy and laser-induced breakdown spectroscopy: Improving ores identification accuracy.

The identification of ore samples is of great scientific significance for mineral exploration, and geological evolution research on the planets. Attri...

In silico investigation on structure-function relationship of members belonging to the human SLC52 transporter family.

Riboflavin is an essential water-soluble vitamin that needs to be provided through the diet because of the conversion into flavin adenine dinucleotide...

Natural language processing and machine learning approaches for food categorization and nutrition quality prediction compared with traditional methods.

BACKGROUND: Food categorization and nutrient profiling are labor intensive, time consuming, and costly tasks, given the number of products and labels ...

Study on the classification and identification of various carbonate and sulfate mineral medicines based on Raman spectroscopy combined with PCA-SVM algorithm.

The efficacy of mineral medicines varies greatly between different origins. Therefore, investigating a method to quickly identify similar mineral medi...