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pro vyhledávání: '"Chang, Howard H."'
Environmental epidemiologic studies routinely utilize aggregate health outcomes to estimate effects of short-term (e.g., daily) exposures that are available at increasingly fine spatial resolutions. However, areal averages are typically used to deriv
Externí odkaz:
http://arxiv.org/abs/2302.02110
Studies of the relationships between environmental exposures and adverse health outcomes often rely on a two-stage statistical modeling approach, where exposure is modeled/predicted in the first stage and used as input to a separately fit health outc
Externí odkaz:
http://arxiv.org/abs/2203.16627
Autor:
Warren, Joshua L., Chang, Howard H., Warren, Lauren K., Strickland, Matthew J., Darrow, Lyndsey A., Mulholland, James A.
Understanding the role of time-varying pollution mixtures on human health is critical as people are simultaneously exposed to multiple pollutants during their lives. For vulnerable sub-populations who have well-defined exposure periods (e.g., pregnan
Externí odkaz:
http://arxiv.org/abs/2104.09730
Fine particulate matter (PM2.5) is a mixture of air pollutants that has adverse effects on human health. Understanding the health effects of PM2.5 mixture and its individual species has been a research priority over the past two decades. However, the
Externí odkaz:
http://arxiv.org/abs/1909.03816
Autor:
Berrocal, Veronica J., Guan, Yawen, Muyskens, Amanda, Wang, Haoyu, Reich, Brian J, Mulholland, James A., Chang, Howard H.
A typical problem in air pollution epidemiology is exposure assessment for individuals for which health data are available. Due to the sparsity of monitoring sites and the limited temporal frequency with which measurements of air pollutants concentra
Externí odkaz:
http://arxiv.org/abs/1904.08931
Ambient fine particulate matter less than 2.5 $\mu$m in aerodynamic diameter (PM$_{2.5}$) has been linked to various adverse health outcomes and has, therefore, gained interest in public health. However, the sparsity of air quality monitors greatly r
Externí odkaz:
http://arxiv.org/abs/1802.03077
Introduction It has been demonstrated that a pathway-based feature selection method which incorporates biological information within pathways into the process of feature selection usually outperform a gene-based feature selection algorithm in terms o
Externí odkaz:
http://arxiv.org/abs/1605.03697
We analyze a recently proposed temporal centrality measure applied to an empirical network based on person-to-person contacts in an emergency department of a busy urban hospital. We show that temporal centrality identifies a distinct set of top-sprea
Externí odkaz:
http://arxiv.org/abs/1601.07586
Introduction: Feature selection and gene set analysis are of increasing interest in bioinformatics. While these two approaches have been developed for different purposes, we describe how some gene set analysis methods can be used to conduct feature s
Externí odkaz:
http://arxiv.org/abs/1511.08272