Abstract Background This Obesity Medicine Association (OMA) Clinical Practice Statement
(CPS) provides clinicians an overview of Artificial Intelligence, focused on the management …

Automated computed tomography (CT) scan segmentation (labelling of pixels according to
tissue type) is now possible. This technique is being adapted to achieve three‐dimensional …

Aims Although obesity is associated with chronic disease, a large section of the population
with high BMI does not have an increased risk of metabolic disease. Increased visceral …

The present review summarizes the available evidence on artificial intelligence (AI)
algorithms aimed to the segmentation of epicardial and pericardial adipose tissues on …

The explosive growth of biomedical Big Data presents both significant opportunities and
challenges in the realm of knowledge discovery and translational applications within …

Objectives To present software for automated adipose tissue quantification of abdominal
magnetic resonance imaging (MRI) data using fully convolutional networks (FCN) and to …

Technologies are transforming the understanding of adipose tissue as a complex and
dynamic tissue that plays a critical role in energy homoeostasis and metabolic health. This …

Background Lowering the dose for positron emission tomography (PET) imaging reduces
patients' radiation burden but decreases the image quality by increasing noise and reducing …

Obesity is a growing public health epidemic worldwide and is implicated in slowing
improved life expectancy and increasing cardiovascular (CV) risk; indeed, several obesity …

Background Quantitative muscle and fat data obtained through body composition analysis
are expected to be a new stable biomarker for the early and accurate prediction of treatment …