ArticleCyborg and bionic systems (Washington, D.C.)2025
BioCompNet: A Deep Learning Workflow Enabling Automated Body Composition Analysis toward Precision Management of Cardiometabolic Disorders.
Article in Cyborg and bionic systems (Washington, D.C.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Multi-task deep learning integrating pretreatment MRI and whole slide images predicts induction chemotherapy response and survival in locally advanced nasopharyngeal carcinoma.PLOS digital health · 2026Article
- Mitochondrial Dysregulation and Molecular Signaling in Systemic Sclerosis Cardiac Disease: An Integrative Echocardiographic, Microvascular, and Biomarker Review.International journal of molecular sciences · 2026Review
- Reduced Coupling of Global Brain Activity and Cerebrospinal Fluid Flow in Individuals With Betel Quid Dependence.Addiction biology · 2026Article
- Associations of muscle mass, adipose tissue mass, and skeletal muscle radiodensity with disease activity in axial spondyloarthritis.Therapeutic advances in musculoskeletal disease · 2026Article
- Multimodal AI in precision medicine: linking omics, imaging and clinical decisions.American journal of clinical and experimental immunology · 2026Article
- Association of early-pregnancy platelet-to-high-density lipoprotein cholesterol ratio with preeclampsia: a retrospective cohort study.American journal of clinical and experimental immunology · 2026Article
- Physics-Informed Neural Networks Meet Multimodal Large Language Models: Biomechanical Simulation in Aortic Aneurysm.Cyborg and bionic systems (Washington, D.C.) · 2026Article
- Heatwave Exposure Accelerates Biological Aging via Metabolic Dysregulation.Cyborg and bionic systems (Washington, D.C.) · 2026Article
- Machine learning for prediction of newly diagnosed atrial fibrillation after emergency percutaneous coronary intervention during hospitalization in patients with acute ST-segment elevation myocardial infarction: a multi-center prospective study.Frontiers in medicine · 2026Article
- Effect of Lifestyle Intervention on the Mobilization of Fat Depots and Organ Iron Deposition in Individuals with Obesity: A Prospective Study.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Growing evidence highlights the importance of body composition (BC), including bone, muscle, and adipose tissue (AT), as a critical biomarker for cardiometabolic risk stratification. However, conventional methods for quantifying BC components using medical images are hindered by labor-intensive workflows and limited anatomical coverage. This study developed BioCompNet-an end-to-end deep learning workflow that integrates dual-parametric magnetic resonance imaging (MRI) sequences (water/fat) with a hierarchical U-Net architecture to enable fully automated quantification of 15 biomechanically critical BC components. BioCompNet targets 10 abdominal compartments (vertebral bone, psoas muscles, core muscles, subcutaneous AT [SAT], superficial SAT, deep SAT, intraperitoneal AT, retroperitoneal AT, visceral AT, and intermuscular AT [IMAT]) and 5 thigh compartments (femur, muscle, SAT, IMAT, and vessels). The workflow was developed on 8,048 MRI slices from a community-based cohort (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.