AIMC Topic: Ethnicity
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Generalized multifactor dimensionality reduction approaches to identification of genetic interactions underlying ordinal traits.
Genetic epidemiology
Nov 2, 2018
The manifestation of complex traits is influenced by gene-gene and gene-environment interactions, and the identification of multifactor interactions is an important but challenging undertaking for genetic studies. Many complex phenotypes such as dise...
Digital Diabetes Data and Artificial Intelligence: A Time for Humility Not Hubris.
Journal of diabetes science and technology
Sep 5, 2018
In the future artificial intelligence (AI) will have the potential to improve outcomes diabetes care. With the creation of new sensors for physiological monitoring sensors and the introduction of smart insulin pens, novel data relationships based on ...
Public Health
Big Data
Decision Support Systems, Clinical
Diabetes Mellitus, Type 2
Genotype
Phenotype
Precision Medicine
Language
Reproducibility of Results
Access to Information
Ethnicity
Data Collection
Racial Groups
Computational Biology
Diabetes Mellitus, Type 1
Decision Making
Healthcare Disparities
Humans
Artificial Intelligence
Word embeddings quantify 100 years of gender and ethnic stereotypes.
Proceedings of the National Academy of Sciences of the United States of America
Apr 3, 2018
Word embeddings are a powerful machine-learning framework that represents each English word by a vector. The geometric relationship between these vectors captures meaningful semantic relationships between the corresponding words. In this paper, we de...
Predictors of firearm violence in urban communities: A machine-learning approach.
Health & place
Mar 14, 2018
Interpersonal firearm violence is a leading cause of death and injuries in the United States. Identifying community characteristics associated with firearm violence is important to improve confounder selection and control in health research, to bette...
Association Between Genotypes and Risk of Cardiovascular Disease in MESA (Multi-Ethnic Study of Atherosclerosis).
Journal of the American Heart Association
Dec 21, 2017
BACKGROUND: genetic variants confer an increased risk for kidney disease. Their associations with cardiovascular disease (CVD) are less certain. We aimed to compare the prevalence of subclinical CVD and incidence of atherosclerotic CVD and heart fai...
Cardiovascular Event Prediction by Machine Learning: The Multi-Ethnic Study of Atherosclerosis.
Circulation research
Aug 9, 2017
RATIONALE: Machine learning may be useful to characterize cardiovascular risk, predict outcomes, and identify biomarkers in population studies.
Racial/Ethnic Disparities in Rates of Traumatic Injury in Arizona, 2011-2012.
Public health reports (Washington, D.C. : 1974)
Aug 22, 2016
OBJECTIVE: The purpose of this study was to compare the rates of traumatic injury among five racial/ethnic groups in Arizona and to identify which mechanisms and intents of traumatic injury were predominant in each group.
Enhancing and Disaggregating Native Hawaiian and Pacific Islander (NHPI) Data Using Natural Language Processing and an Expanded Race/Ethnicity Lexicon.
Studies in health technology and informatics
Aug 7, 2025
Native Hawaiian and Pacific Islander (NHPI) populations are often aggregated into broad racial categories, obscuring potential disparities. This study leverages an expanded race/ethnicity lexicon and natural language processing (NLP) to identify docu...
Evaluating Algorithmic Approaches to Uncover Racial, Ethnic, and Gender Disparities in Scientific Authorship.
American journal of public health
Jul 1, 2025
To explore the capabilities of race/ethnicity and gender prediction algorithms in uncovering patterns of authorship distribution in scientific paper submissions to a major peer-reviewed scientific journal (), we analyzed 17 667 manuscript submissions...
Assessing the Global Impact of Brain Small Vessel Disease on Cognition: The Multi-Ethnic Study of Atherosclerosis.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Jun 1, 2025
INTRODUCTION: We aimed to examine the global impact of brain small vessel disease (SVD) on cognitive performance.
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