Metabolic phenotyping with computed tomography deep learning for metabolic syndrome, osteoporosis and sarcopenia predicts mortality in adults.
Sang Wouk ChoSeungjin BaekSookyeong HanChang Oh KimHyeon Chang KimYumie RheeNamki HongPublished in: Journal of cachexia, sarcopenia and muscle (2024)
A CT body composition-based MLP model detected MS, osteoporosis and sarcopenia simultaneously in community-dwelling and hospitalized adults. Metabolic phenotypes predicted by the CT MLP model were associated with long-term mortality, independent of covariates.
Keyphrases
- community dwelling
- body composition
- computed tomography
- bone mineral density
- dual energy
- image quality
- metabolic syndrome
- postmenopausal women
- deep learning
- contrast enhanced
- positron emission tomography
- cardiovascular events
- resistance training
- skeletal muscle
- risk factors
- mass spectrometry
- multiple sclerosis
- high throughput
- ms ms
- machine learning
- insulin resistance
- cardiovascular disease
- type diabetes
- uric acid
- pet ct