dual-energy X-ray absorptiometry
PulseAugur coverage of dual-energy X-ray absorptiometry — every cluster mentioning dual-energy X-ray absorptiometry across labs, papers, and developer communities, ranked by signal.
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New Graph Neural Regression Framework Accurately Estimates Body Composition
Researchers have developed a new framework called target-aware, state-adaptive $p$-Dirichlet energy-flow graph neural regression ($p$SADE-GNR) for estimating body composition from non-invasive measurements. This method …
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Google Research uses smartphone photos to estimate metabolic risk
Google Research has developed PhotoScan, a deep learning framework that estimates body composition metrics like body fat percentage, Android-to-Gynoid fat ratio, and Visceral-to-Subcutaneous fat ratio using standard sma…
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AI model LeDXA extracts disease risk and biological age from X-ray scans
Researchers have developed LeDXA, a self-supervised learning model that extracts health insights from dual-energy X-ray absorptiometry (DXA) scans. Trained on unlabeled DXA images, LeDXA predicts disease risk, biologica…
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AI models outperform FRAX in predicting fracture risk using EHR and DXA data
Researchers have developed and validated new models for predicting fracture risk in adults over 50, utilizing data from dual-energy X-ray absorptiometry (DXA) and electronic health records (EHR). These models, including…
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New causal analysis method improves hip fracture risk prediction
Researchers have developed a causal analysis method to better understand the relationship between skeletal phenotypes derived from DXA scans and the risk of hip fractures. By analyzing data from over 21,000 UK Biobank p…
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VerteNet hybrid CNN Transformer improves DXA scan landmark localization
Researchers have developed VerteNet, a hybrid CNN-Transformer model designed to accurately pinpoint vertebral landmarks in lateral spine DXA scans. This deep learning framework addresses challenges posed by low-contrast…