AIMC Topic: Adipose Tissue

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A novel approach to dry weight adjustments for dialysis patients using machine learning.

PloS one
BACKGROUND AND AIMS: Knowledge of the proper dry weight plays a critical role in the efficiency of dialysis and the survival of hemodialysis patients. Recently, bioimpedance spectroscopy(BIS) has been widely used for set dry weight in hemodialysis pa...

Coupling Machine Learning and Lipidomics as a Tool to Investigate Metabolic Dysfunction-Associated Fatty Liver Disease. A General Overview.

Biomolecules
Hepatic biopsy is the gold standard for staging nonalcoholic fatty liver disease (NAFLD). Unfortunately, accessing the liver is invasive, requires a multidisciplinary team and is too expensive to be conducted on large segments of the population. NAFL...

Deep Learning Automated Segmentation for Muscle and Adipose Tissue from Abdominal Computed Tomography in Polytrauma Patients.

Sensors (Basel, Switzerland)
Manual segmentation of muscle and adipose compartments from computed tomography (CT) axial images is a potential bottleneck in early rapid detection and quantification of sarcopenia. A prototype deep learning neural network was trained on a multi-cen...

3D microscopy and deep learning reveal the heterogeneity of crown-like structure microenvironments in intact adipose tissue.

Science advances
Crown-like structures (CLSs) are adipose microenvironments of macrophages engulfing adipocytes. Their histological density in visceral adipose tissue (VAT) predicts metabolic disorder progression in obesity and is believed to initiate obesity comorbi...

Robust water-fat separation based on deep learning model exploring multi-echo nature of mGRE.

Magnetic resonance in medicine
PURPOSE: To design a new deep learning network for fast and accurate water-fat separation by exploring the correlations between multiple echoes in multi-echo gradient-recalled echo (mGRE) sequence and evaluate the generalization capabilities of the n...

Bone Mineral Density and Content Among Patients With Coronary Artery Disease: A Comparative Study.

The American journal of the medical sciences
INTRODUCTION: Some studies indicate an association between coronary artery disease (CAD) and osteoporosis. This case-control study examined the association between body composition and bone mineral content (BMC) and density (BMD) among patients with ...

[Epicardial fat Tissue Volumetry: Comparison of Semi-Automatic Measurement and the Machine Learning Algorithm].

Kardiologiia
Aim        To compare assessments of epicardial adipose tissue (EAT) volumes obtained with a semi-automatic, physician-performed analysis and an automatic analysis using a machine-learning algorithm by data of low-dose (LDCT) and standard computed to...

Using an improved relative error support vector machine for body fat prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The term 'obesity' refers to excessive body fat, and it is a chronic disease associated with various complications. Although a range of techniques for body fat estimation have been developed to assess obesity, they are typic...

Automatic Vertebral Body Segmentation Based on Deep Learning of Dixon Images for Bone Marrow Fat Fraction Quantification.

Frontiers in endocrinology
Bone marrow fat (BMF) fraction quantification in vertebral bodies is used as a novel imaging biomarker to assess and characterize chronic lower back pain. However, manual segmentation of vertebral bodies is time consuming and laborious. (1) Develop...