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Identifying Cases of Metastatic Prostate Cancer Using Machine Learning on Electronic Health Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Cancer stage is rarely captured in structured form in the electronic health record (EHR). We evaluate the performance of a classifier, trained on structured EHR data, in identifying prostate cancer patients with metastatic disease. Using EHR data for...

Application of machine-learning to predict early spontaneous preterm birth among nulliparous non-Hispanic black and white women.

Annals of epidemiology
PURPOSE: Spontaneous preterm birth is a leading cause of perinatal mortality in the United States, occurring disproportionately among non-Hispanic black women compared to other race-ethnicities. Clinicians lack tools to identify first-time mothers at...

Space-time trends of PM constituents in the conterminous United States estimated by a machine learning approach, 2005-2015.

Environment international
Particulate matter with aerodynamic diameter less than 2.5 μm (PM) is a complex mixture of chemical constituents emitted from various emission sources or through secondary reactions/processes; however, PM is regulated mostly based on its total mass c...

A machine learning approach to investigate potential risk factors for gastroschisis in California.

Birth defects research
BACKGROUND: To generate new leads about risk factors for gastroschisis, a birth defect that has been increasing in prevalence over time, we performed an untargeted data mining statistical approach.

Using natural language processing and machine learning to classify health literacy from secure messages: The ECLIPPSE study.

PloS one
Limited health literacy is a barrier to optimal healthcare delivery and outcomes. Current measures requiring patients to self-report limitations are time-consuming and may be considered intrusive by some. This makes widespread classification of patie...

Cluster-based bagging of constrained mixed-effects models for high spatiotemporal resolution nitrogen oxides prediction over large regions.

Environment international
BACKGROUND: Accurate estimation of nitrogen dioxide (NO) and nitrogen oxide (NO) concentrations at high spatiotemporal resolutions is crucial for improving evaluation of their health effects, particularly with respect to short-term exposures and acut...

Understanding mixed environmental exposures using metabolomics via a hierarchical community network model in a cohort of California women in 1960's.

Reproductive toxicology (Elmsford, N.Y.)
Even though the majority of population studies in environmental health focus on a single factor, environmental exposure in the real world is a mixture of many chemicals. The concept of "exposome" leads to an intellectual framework of measuring many e...