AIMC Topic: Body Composition
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Markers of body fat, the mediating role of alanine aminotransferase, and their association with the risk of metabolic dysfunction-associated steatotic liver disease.
European journal of pediatrics
Aug 2, 2025
Metabolic dysfunction-associated steatotic liver disease (MASLD) in children with obesity correlates with metabolic dysfunction, yet interactions between anthropometrics, liver enzymes, and risk of MASLD remain unclear. This study included 219 childr...
Computed tomography-derived quantitative imaging biomarkers enable the prediction of disease manifestations and survival in patients with systemic sclerosis.
RMD open
Jun 25, 2025
INTRODUCTION: Systemic sclerosis (SSc) is a complex inflammatory vasculopathy with diverse symptoms and variable disease progression. Despite its known impact on body composition (BC), clinical decision-making has yet to incorporate these biomarkers....
Evaluation of semi-automated versus fully automated technologies for computed tomography scalable body composition analyses in patients with severe acute respiratory syndrome Coronavirus-2.
Clinical nutrition ESPEN
Jun 11, 2025
RATIONALE AND OBJECTIVES: Fully automated, artificial intelligence (AI) -based software has recently become available for scalable body composition analysis. Prior to broad application in the clinical arena, validation studies are needed. Our goal wa...
Machine learning-based prediction of respiratory depression during sedation for liposuction.
Scientific reports
Jun 4, 2025
Procedural sedation is often performed by non-anesthesiologists in various settings and can lead to respiratory depression. A tool that enables early detection of respiratory compromise could not only enhance patient safety during procedural sedation...
Exchange of Quantitative Computed Tomography Assessed Body Composition Data Using Fast Healthcare Interoperability Resources as a Necessary Step Toward Interoperable Integration of Opportunistic Screening Into Clinical Practice: Methodological Development Study.
Journal of medical Internet research
May 21, 2025
BACKGROUND: Fast Healthcare Interoperability Resources (FHIR) is a widely used standard for storing and exchanging health care data. At the same time, image-based artificial intelligence (AI) models for quantifying relevant body structures and organs...
AI-based volumetric six-tissue body composition quantification from CT cardiac attenuation scans for mortality prediction: a multicentre study.
The Lancet. Digital health
May 16, 2025
BACKGROUND: CT attenuation correction (CTAC) scans are routinely obtained during cardiac perfusion imaging, but currently only used for attenuation correction and visual calcium estimation. We aimed to develop a novel artificial intelligence (AI)-bas...
Development and validation of machine learning models for predicting low muscle mass in patients with obesity and diabetes.
Lipids in health and disease
Apr 29, 2025
BACKGROUND AND AIMS: Low muscle mass (LMM) is a critical complication in patients with obesity and diabetes, exacerbating metabolic and cardiovascular risks. Novel obesity indices, such as the body roundness index (BRI), conicity index, and relative ...
GDM-BC: Non-invasive body composition dataset for intelligent prediction of Gestational Diabetes Mellitus.
Computers in biology and medicine
Apr 23, 2025
Gestational Diabetes Mellitus (GDM) refers to any degree of impaired glucose tolerance with onset or first recognition during pregnancy. As a high-prevalence disease, GDM damages the health of both pregnant women and fetuses in the short and long ter...
Optimizing Nutritional Care with Machine Learning: Identifying Sarcopenia Risk Through Body Composition Parameters in Cancer Patients-Insights from the NUTritional and Sarcopenia RIsk SCREENing Project (NUTRISCREEN).
Nutrients
Apr 18, 2025
: Cancer and related treatments can impair body composition (BC), increasing the risk of malnutrition and sarcopenia, poor prognosis, and Health-Related Quality of Life (HRQoL). To enhance BC parameter interpretation through Bioelectrical Impedance A...
Validation of body composition parameters extracted via deep learning-based segmentation from routine computed tomographies.
Scientific reports
Apr 7, 2025
Sarcopenia and body composition metrics are strongly associated with patient outcomes. In this study, we developed and validated a flexible, open-access pipeline integrating available deep learning-based segmentation models with pre- and postprocessi...
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