AIMC Topic: Nutrition Surveys
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Unveiling the effect of urinary xenoestrogens on chronic kidney disease in adults: A machine learning model.
Ecotoxicology and environmental safety
Feb 22, 2025
Exposure to three primary xenoestrogens (XEs), including phthalates, parabens, and phenols, has been strongly associated with chronic kidney disease (CKD). An interpretable machine learning (ML) model was developed to predict CKD using data from the ...
Identifying major depressive disorder among US adults living alone using stacked ensemble machine learning algorithms.
Frontiers in public health
Feb 21, 2025
BACKGROUND: It has been increasingly recognized that adults living alone have a higher likelihood of developing Major Depressive Disorder (MDD) than those living with others. However, there is still no prediction model for MDD specifically designed f...
Prediction of depressive disorder using machine learning approaches: findings from the NHANES.
BMC medical informatics and decision making
Feb 17, 2025
BACKGROUND: Depressive disorder, particularly major depressive disorder (MDD), significantly impact individuals and society. Traditional analysis methods often suffer from subjectivity and may not capture complex, non-linear relationships between ris...
Machine learning modeling for predicting adherence to physical activity guideline.
Scientific reports
Feb 15, 2025
This study aims to create predictive models for PA guidelines by using ML and examine the critical determinants influencing adherence to the PA guidelines. 11,638 entries from the National Health and Nutrition Examination Survey were analyzed. Variab...
Machine learning prediction of glaucoma by heavy metal exposure: results from the National Health and Nutrition Examination Survey 2005 to 2008.
Scientific reports
Feb 10, 2025
Using follow-up data from the National Health and Nutrition Examination Survey (NHANES) database, we have collected information on 2572 subjects and used generalized linear model to investigate the association between urinary heavy metal levels and g...
Discovering Vitamin-D-Deficiency-Associated Factors in Korean Adults Using KNHANES Data Based on an Integrated Analysis of Machine Learning and Statistical Techniques.
Nutrients
Feb 8, 2025
: Vitamin D deficiency (VDD) is a global health concern associated with metabolic disease and immune dysfunction. Despite known risk factors like limited sun exposure, diet, and lifestyle, few studies have explored these factors comprehensively on a ...
Assessing the diagnostic accuracy of machine learning algorithms for identification of asthma in United States adults based on NHANES dataset.
Scientific reports
Feb 6, 2025
Asthma diagnosis poses challenges due to underreporting of symptoms, misdiagnoses, and limitations in existing diagnostic tests. Machine learning (ML) offers a promising avenue for addressing these challenges by leveraging demographic and clinical da...
Development of a machine learning model related to explore the association between heavy metal exposure and alveolar bone loss among US adults utilizing SHAP: a study based on NHANES 2015-2018.
BMC public health
Feb 4, 2025
BACKGROUND: Alveolar bone loss (ABL) is common in modern society. Heavy metal exposure is usually considered to be a risk factor for ABL. Some studies revealed a positive trend found between urinary heavy metals and periodontitis using multiple logis...
Unlocking the link: predicting cardiovascular disease risk with a focus on airflow obstruction using machine learning.
BMC medical informatics and decision making
Feb 3, 2025
BACKGROUND: Respiratory diseases and Cardiovascular Diseases (CVD) often coexist, with airflow obstruction (AO) severity closely linked to CVD incidence and mortality. As both conditions rise, early identification and intervention in risk populations...
Machine Learning Analysis of Nutrient Associations with Peripheral Arterial Disease: Insights from NHANES 1999-2004.
Annals of vascular surgery
Jan 30, 2025
BACKGROUND: Peripheral arterial disease (PAD) is a common manifestation of atherosclerosis, affecting over 200 million people worldwide. The incidence of PAD is increasing due to the aging population. Common risk factors include smoking, diabetes, an...
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