AIMC Topic: Body Composition

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Advances in digital anthropometric body composition assessment: neural network algorithm prediction of appendicular lean mass.

European journal of clinical nutrition
Currently available anthropometric body composition prediction equations were often developed on small participant samples, included only several measured predictor variables, or were prepared using conventional statistical regression methods. Machin...

Validation of a Novel Perceptual Body Image Assessment Method Using Mobile Digital Imaging Analysis: A Cross-Sectional Multicenter Evaluation in a Multiethnic Sample.

Behavior therapy
Given that mobile digital imaging analyses (DIA) are equipped to automate body composition and subsequently alter one's appearance at a given objective body fat percent (BF%), the purpose of this study was to validate the use of this tool for assessm...

Early prediction of body composition parameters on metabolically unhealthy in the Chinese population via advanced machine learning.

Frontiers in endocrinology
BACKGROUND: Metabolic syndrome (Mets) is considered a global epidemic of the 21st century, predisposing to cardiometabolic diseases. This study aims to describe and compare the body composition profiles between metabolic healthy (MH) and metabolic un...

Comparison of computed tomography and dual-energy X-ray absorptiometry in the evaluation of body composition in patients with obesity.

Frontiers in endocrinology
OBJECTIVE: a) To evaluate the accuracy of the pre-existing equations (based on cm2 provided by CT images), to estimate in kilograms (Kg) the body composition (BC) in patients with obesity (PwO), by comparison with Dual-energy X-ray absorptiometry (DX...

Body composition predicts hypertension using machine learning methods: a cohort study.

Scientific reports
We used machine learning methods to investigate if body composition indices predict hypertension. Data from a cohort study was used, and 4663 records were included (2156 were male, 1099 with hypertension, with the age range of 35-70 years old). Body ...

Deep learning of image-derived measures of body composition in pediatric, adolescent, and young adult lymphoma: association with late treatment effects.

European radiology
OBJECTIVES: The objective of this study was to translate a deep learning (DL) approach for semiautomated analysis of body composition (BC) measures from standard of care CT images to investigate the prognostic value of BC in pediatric, adolescent, an...

Predicting outcomes of continuous renal replacement therapy using body composition monitoring: a deep-learning approach.

Scientific reports
Fluid balance is a critical prognostic factor for patients with severe acute kidney injury (AKI) requiring continuous renal replacement therapy (CRRT). This study evaluated whether repeated fluid balance monitoring could improve prognosis in this cli...

The association of radiologic body composition parameters with clinical outcomes in level-1 trauma patients.

European journal of trauma and emergency surgery : official publication of the European Trauma Society
PURPOSE: The present study aims to assess whether CT-derived muscle mass, muscle density, and visceral fat mass are associated with in-hospital complications and clinical outcome in level-1 trauma patients.

Artificial intelligence and body composition.

Diabetes & metabolic syndrome
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 adiposity and sarcopenia are also risk factors for metabolic disease i...

Technical Adequacy of Fully Automated Artificial Intelligence Body Composition Tools: Assessment in a Heterogeneous Sample of External CT Examinations.

AJR. American journal of roentgenology
Clinically usable artificial intelligence (AI) tools analyzing imaging studies should be robust to expected variations in study parameters. The purposes of this study were to assess the technical adequacy of a set of automated AI abdominal CT body ...