Machine learning model for depression based on heavy metals among aging people: A study with National Health and Nutrition Examination Survey 2017–2018
出版年份 2022 全文链接
标题
Machine learning model for depression based on heavy metals among aging people: A study with National Health and Nutrition Examination Survey 2017–2018
作者
关键词
-
出版物
Frontiers in Public Health
Volume 10, Issue -, Pages -
出版商
Frontiers Media SA
发表日期
2022-08-04
DOI
10.3389/fpubh.2022.939758
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Environmental science and pollution research role of heavy metal concentrations and vitamin intake from food in depression: a national cross-sectional study (2009–2017)
- (2021) Hai Duc Nguyen et al. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
- Comparison of machine learning and logistic regression models in predicting acute kidney injury: A systematic review and meta-analysis
- (2021) Xuan Song et al. INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
- A Deep Learning Algorithm to Predict Hazardous Drinkers and the Severity of Alcohol-Related Problems Using K-NHANES
- (2021) Suk-Young Kim et al. Frontiers in Psychiatry
- Blood volatile organic aromatic compounds concentrations across adulthood in relation to total and cause specific mortality: A prospective cohort study
- (2021) Wenzhen Li et al. CHEMOSPHERE
- Association of polycyclic aromatic hydrocarbons exposure, systemic inflammation with hearing loss among adults and adolescents
- (2021) Wenzhen Li et al. ENVIRONMENTAL POLLUTION
- Association of Blood Mercury Level with the Risk of Depression According to Fish Intake Level in the General Korean Population: Findings from the Korean National Health and Nutrition Examination Survey (KNHANES) 2008–2013
- (2020) Kyung Won Kim et al. Nutrients
- An Interpretable Prediction Model for Identifying N7-Methylguanosine Sites Based on XGBoost and SHAP
- (2020) Yue Bi et al. Molecular Therapy-Nucleic Acids
- Low Zinc, Copper, and Manganese Intake is Associated with Depression and Anxiety Symptoms in the Japanese Working Population: Findings from the Eating Habit and Well-Being Study
- (2019) Mieko Nakamura et al. Nutrients
- Identifying depression in the National Health and Nutrition Examination Survey data using a deep learning algorithm
- (2019) Jihoon Oh et al. JOURNAL OF AFFECTIVE DISORDERS
- Age and sex differences in hearing loss association with depressive symptoms: analyses of NHANES 2011–2012
- (2018) Franco Scinicariello et al. PSYCHOLOGICAL MEDICINE
- Environmental exposure to pesticides and the risk of Parkinson's disease in the Netherlands
- (2017) Maartje Brouwer et al. ENVIRONMENT INTERNATIONAL
- Cadmium, Lead, and Depressive Symptoms
- (2017) Melanie C. Buser et al. JOURNAL OF CLINICAL PSYCHIATRY
- Blood cadmium and depressive symptoms: Confounded by cigarette smoking
- (2017) Danielle E. Kostrubiak et al. PSYCHIATRY RESEARCH
- Multicenter Comparison of Machine Learning Methods and Conventional Regression for Predicting Clinical Deterioration on the Wards
- (2016) Matthew M. Churpek et al. CRITICAL CARE MEDICINE
- Blood cadmium and depressive symptoms in young adults (aged 20–39 years)
- (2014) F. Scinicariello et al. PSYCHOLOGICAL MEDICINE
- Pop, heavy metal and the blues: secondary analysis of persistent organic pollutants (POP), heavy metals and depressive symptoms in the NHANES National Epidemiological Survey
- (2014) M. Berk et al. BMJ Open
- Total Blood Mercury Levels and Depression among Adults in the United States: National Health and Nutrition Examination Survey 2005–2008
- (2013) Tsz Hin H. Ng et al. PLoS One
- Correlation of magnesium intake with metabolic parameters, depression and physical activity in elderly type 2 diabetes patients: a cross-sectional study
- (2012) Jui-Hua Huang et al. Nutrition Journal
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