Prevalent metabolic syndrome
1 paper1 finding
- Humans1
Associations
1Ensemble machine learning model
upin humans1
1 study
Ensemble machine learning model
upin humans1
ensemble machine learning model predicts prevalent metabolic syndrome in humans (AUC 0.751, 95% CI 0.731–0.771).
“Ensemble achieved the highest mean AUC (0.751, 95% CI 0.731-0.771)”
HumansNatural-prevalence cohort; stratified 10-fold cross-validationn = 1,674
Non-Invasive Prediction of Metabolic Syndrome Using Explainable Machine Learning
Diagnostics (Basel, Switzerland)22 Sep 2026
Latest
6 in 12 monthsDiagnostics
Non-Invasive Prediction of Metabolic Syndrome Using Explainable Machine Learning
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Acta Diabetologica
Unmasking covert metabolic syndrome in normal-weight women: regional adiposity and muscle quality outperform BMI in a temporally validated machine learning triage framework
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Cureus
Ethnicity-Specific Thyroid Hormone Sensitivity Indices and Their Association With Metabolic Syndrome in Euthyroid South Asian Adults
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Clinical sub-phenotypes of co-occurring metabolic syndrome and pre-frailty and their associated factors in older adults: findings from Whitehall II study
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Associations of long-term PM2.5 exposure and genetic susceptibility with prevalent metabolic syndrome and subsequent cardiovascular disease risk: A UK Biobank cohort study
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Cross-sectional evaluation of cardiovascular biological age using point-of-care ultrasound
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