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Body Composition

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Aerobic Fitness is a Predictor of Body Composition in Women With Breast Cancer at Diagnosis.

Clinical breast cancer
BACKGROUND: The objective of this study was to investigate the relationship of aerobic fitness (AF) at diagnosis, before treatment and its relationship with body composition, physical function, lipidic profile, comorbidities, tumor characteristics, a...

Genetic architecture of 11 organ traits derived from abdominal MRI using deep learning.

eLife
Cardiometabolic diseases are an increasing global health burden. While socioeconomic, environmental, behavioural, and genetic risk factors have been identified, a better understanding of the underlying mechanisms is required to develop more effective...

Automated Measurements of Body Composition in Abdominal CT Scans Using Artificial Intelligence Can Predict Mortality in Patients With Cirrhosis.

Hepatology communications
Body composition measures derived from already available electronic medical records (computed tomography [CT] scans) can have significant value, but automation of measurements is needed for clinical implementation. We sought to use artificial intelli...

Deep neural network for automatic volumetric segmentation of whole-body CT images for body composition assessment.

Clinical nutrition (Edinburgh, Scotland)
BACKGROUND & AIMS: Body composition analysis on CT images is a valuable tool for sarcopenia assessment. We aimed to develop and validate a deep neural network applicable to whole-body CT images of PET-CT scan for the automatic volumetric segmentation...

Pixel-wise body composition prediction with a multi-task conditional generative adversarial network.

Journal of biomedical informatics
The analysis of human body composition plays a critical role in health management and disease prevention. However, current medical technologies to accurately assess body composition such as dual energy X-ray absorptiometry, computed tomography, and m...

Predicting carcass cut yields in cattle from digital images using artificial intelligence.

Meat science
Deep Learning (DL) has proven to be a successful tool for many image classification problems but has yet to be applied to carcass images. The aim of this study was to train DL models to predict carcass cut yields and compare predictions to more stand...

Detection of sarcopenic obesity and prediction of long-term survival in patients with gastric cancer using preoperative computed tomography and machine learning.

Journal of surgical oncology
BACKGROUND: Previous studies evaluating the prognostic value of computed tomography (CT)-derived body composition data have included few patients. Thus, we assessed the prevalence and prognostic value of sarcopenic obesity in a large population of ga...

Whole-body Composition Profiling Using a Deep Learning Algorithm: Influence of Different Acquisition Parameters on Algorithm Performance and Robustness.

Investigative radiology
OBJECTIVES: To develop, test, and validate a body composition profiling algorithm for automated segmentation of body compartments in whole-body magnetic resonance imaging (wbMRI) and to investigate the influence of different acquisition parameters on...