AIMC Topic: United States

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Characterizing Autoimmune Disease-associated Diffuse Large B-cell Lymphoma in a SEER-Medicare Cohort.

Clinical lymphoma, myeloma & leukemia
BACKGROUND: Severe immune dysregulation such as seen in autoimmune (AI) disease is known to act as a significant risk factor for diffuse large B-cell lymphoma (DLBCL). However, little is known about the demographics or clinical outcomes of DLBCL that...

Vitamin D Deficiency and Atopic Dermatitis: Consider Disease, Race, and Body Mass.

Skinmed
Vitamin D deficiency causes rickets, but has been associated with various diseases, including atopic dermatitis (AD). This study analyzes serum vitamin D in pediatric medical center patients with AD and potential confounding factors. At Cardinal Glen...

Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States.

Proceedings of the National Academy of Sciences of the United States of America
The United States spends more than $250 million each year on the American Community Survey (ACS), a labor-intensive door-to-door study that measures statistics relating to race, gender, education, occupation, unemployment, and other demographic facto...

Forecasting carbon dioxide emissions based on a hybrid of mixed data sampling regression model and back propagation neural network in the USA.

Environmental science and pollution research international
The accurate forecast of carbon dioxide emissions is critical for policy makers to take proper measures to establish a low carbon society. This paper discusses a hybrid of the mixed data sampling (MIDAS) regression model and BP (back propagation) neu...

Comparing clinician descriptions of frailty and geriatric syndromes using electronic health records: a retrospective cohort study.

BMC geriatrics
BACKGROUND: Geriatric syndromes, including frailty, are common in older adults and associated with adverse outcomes. We compared patients described in clinical notes as "frail" to other older adults with respect to geriatric syndrome burden and healt...

Development of A Machine Learning Algorithm to Classify Drugs Of Unknown Fetal Effect.

Scientific reports
Many drugs commonly prescribed during pregnancy lack a fetal safety recommendation - called FDA 'category C' drugs. This study aims to classify these drugs into harmful and safe categories using knowledge gained from chemoinformatics (i.e., pharmacol...

Risk prediction model for in-hospital mortality in women with ST-elevation myocardial infarction: A machine learning approach.

Heart & lung : the journal of critical care
BACKGROUND: Studies had shown that mortality due to ST-elevation myocardial infarction (STEMI) is higher in women compared with men. The purpose of this study is to develop and validate prediction models for all-cause in-hospital mortality in women a...

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

Environmental health : a global access science source
BACKGROUND: There is growing concern of health effects of exposure to pollutant mixtures. We initially proposed an Environmental Risk Score (ERS) as a summary measure to examine the risk of exposure to multi-pollutants in epidemiologic research consi...