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- W3136001107 abstract "Rates of preterm birth and low birthweight continue to rise in the United States and pose a significant public health problem. Although a variety of environmental exposures are known to contribute to these and other adverse birth outcomes, there has been a limited success in developing policies to prevent these outcomes. A better characterization of the complexities between multiple exposures and their biological responses can provide the evidence needed to inform public health policy and strengthen preventative population-level interventions. In order to achieve this, we encourage the establishment of an interdisciplinary data science framework that integrates epidemiology, toxicology and bioinformatics with biomarker-based research to better define how population-level exposures contribute to these adverse birth outcomes. The proposed interdisciplinary research framework would 1) facilitate data-driven analyses using existing data from health registries and environmental monitoring programs; 2) develop novel algorithms with the ability to predict which exposures are driving, in this case, adverse birth outcomes in the context of simultaneous exposures; and 3) refine biomarker-based research, ultimately leading to new policies and interventions to reduce the incidence of adverse birth outcomes." @default.
- W3136001107 created "2021-03-29" @default.
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- W3136001107 date "2021-06-01" @default.
- W3136001107 modified "2023-10-04" @default.
- W3136001107 title "Interdisciplinary data science to advance environmental health research and improve birth outcomes" @default.
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- W3136001107 doi "https://doi.org/10.1016/j.envres.2021.111019" @default.
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