Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES.

about

Evaluating effects of prenatal exposure to phthalate mixtures on birth weight: A comparison of three statistical approaches.Associations between mixtures of urinary phthalate metabolites with gestational age at delivery: a time to event analysis using summative phthalate risk scores.

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P2860

Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES.

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2017 nî lūn-bûn

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Construction of environmental ...... diovascular disease in NHANES.

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Construction of environmental ...... diovascular disease in NHANES.

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Construction of environmental ...... diovascular disease in NHANES.

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Construction of environmental ...... diovascular disease in NHANES.

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Bhramar Mukherjee

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Sung Kyun Park

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Zhangchen Zhao

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P2860

Metals in urine and peripheral arterial disease.

Urinary creatinine concentrations in the U.S. population: implications for urinary biologic monitoring measurements

Gamma-Glutamyltransferase: A Predictive Biomarker of Cellular Antioxidant Inadequacy and Disease Risk

The exposome: from concept to utility

Metal pollutants and cardiovascular disease: mechanisms and consequences of exposure

Cadmium exposure and clinical cardiovascular disease: a systematic review

Metals in Urine and Diabetes in U.S. Adults

Statistical Approaches for Assessing Health Effects of Environmental Chemical Mixtures in Epidemiology: Lessons from an Innovative Workshop

To Explain or to Predict?

Exposure measurement error in time-series studies of air pollution: concepts and consequences

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s12940-017-0310-9

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10.1186/S12940-017-0310-9

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Sung Kyun Park

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National Institute for Occupational Safety and Health

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cardiovascular disease

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biomarker

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Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES.

about

P2860

P2860

Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES.

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