AIMC Topic: Nutrition Surveys
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Associations of the Hs-CRP/HDL-C ratio with stroke among US adults: Evidence from NHANES 2015-2018.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Aug 1, 2025
BACKGROUND: The high-sensitivity C-reactive protein (Hs-CRP)-to-high-density lipoprotein cholesterol (HDL-C) ratio, which integrates insights into inflammation and lipid metabolism, serves as a comprehensive indicator. The association between this ra...
Development and validation of an interpretable machine learning model for predicting hyperuricemia risk: Based on environmental chemical exposure.
Ecotoxicology and environmental safety
Jul 1, 2025
Hyperuricemia is a global health concern, with environmental chemicals as risk factors. This study used data of multiple environmental chemical exposures from the 2011-2012 cycle of the National Health and Nutrition Examination Survey (NHANES) to dev...
Enhancing osteoporosis risk prediction using machine learning: A holistic approach integrating biomarkers and clinical data.
Computers in biology and medicine
Jun 1, 2025
Osteoporosis (OP) affects approximately 18 % of the global population, with osteoporosis-associated fractures impacting up to 37 million people annually. While dual-energy X-ray absorptiometry (DXA) remains the gold standard for diagnosis, its limita...
Machine learning-based prediction of hearing loss: Findings of the US NHANES from 2003 to 2018.
Hearing research
Jun 1, 2025
The prevalence of hearing loss (HL) has emerged as an escalating public health concern globally. The objective of this study was to leverage data from the National Health and Nutritional Examination Survey (NHANES) to develop an interpretable predict...
Application of machine learning algorithms in osteoporosis analysis based on cardiovascular health assessed by life's essential 8: a cross-sectional study.
Journal of health, population, and nutrition
May 29, 2025
BACKGROUND: Life's Essential 8 (LE8) for assessing cardiovascular health (CVH) has been demonstrated to be inversely associated with osteoporosis (OP). This study aims to create a machine learning (ML) model to assess the clinical association value o...
Prediction of coronary heart disease based on klotho levels using machine learning.
Scientific reports
May 27, 2025
The diagnostic accuracy for coronary heart disease (CHD) needs to be improved. Some studies have indicated that klotho protein levels upon admission comprise an independent risk factor for CHD and have clinical value for predicting CHD. This study ai...
Machine learning prediction model with shap interpretation for chronic bronchitis risk assessment based on heavy metal exposure: a nationally representative study.
BMC pulmonary medicine
May 22, 2025
BACKGROUND: Chronic bronchitis (CB), as a core precursor of Chronic Obstructive Pulmonary Disease (COPD), is crucial for global disease burden prevention and control. Although the association between heavy metal exposure and respiratory damage has be...
Deep learning health space model for ordered responses.
BMC medical informatics and decision making
May 16, 2025
BACKGROUND: As personalized medicine becomes more prevalent, the objective measurement and visualization of an individual's health status are becoming increasingly crucial. However, as the dimensions of data collected from each individual increase, t...
Long Short-Term Memory Network for Accelerometer-Based Hypertension Classification.
Studies in health technology and informatics
May 15, 2025
This study investigates the application of a Long Short-Term Memory (LSTM) architecture for classifying hypertension using accelerometer data, specifically focusing on physical activity and sleep from the publicly available NHANES 2011-2012 dataset. ...
Machine learning for predicting all-cause mortality of metabolic dysfunction-associated fatty liver disease: a longitudinal study based on NHANES.
BMC gastroenterology
May 15, 2025
BACKGROUND: The mortality burden of metabolic dysfunction-associated fatty liver disease (MAFLD) is rising, making it crucial to predict mortality and identify the factors influencing it. While advanced machine learning algorithms are gaining recogni...
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