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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 2 of 2 Research Studies DisplayedYoon S, Odlum M, Lee Y
Applying deep learning to understand predictors of tooth mobility among urban Latinos.
In this study, the investigators applied deep learning algorithms to build correlate models that predicted tooth mobility in a convenience sample of urban Latinos. The authors suggest that their application was useful for gaining insights into the most important modifiable and non-modifiable factors predicting tooth mobility, and maybe useful for guiding targeted interventions in urban Latinos.
AHRQ-funded; HS019853.
Citation: Yoon S, Odlum M, Lee Y .
Applying deep learning to understand predictors of tooth mobility among urban Latinos.
Stud Health Technol Inform 2018;251:241-44..
Keywords: Dental and Oral Health, Elderly, Racial and Ethnic Minorities, Urban Health
Yoon S, Choi T, Odlum M
Machine learning to identify behavioral determinants of oral health in inner city older Hispanic adults.
In this study, the investigators applied machine learning techniques to a community-based behavioral dataset to build prediction models to gain insights about minority dental health and population aging as the foundation for future interventions for urban Hispanics. Their application of machine learning techniques identified emotional and systemic factors such as chronic stress and health literacy as the strongest predictors of self-reported dental health among hundreds of possible variables.
AHRQ-funded; HS019853.
Citation: Yoon S, Choi T, Odlum M .
Machine learning to identify behavioral determinants of oral health in inner city older Hispanic adults.
Stud Health Technol Inform 2018;251:253-56..
Keywords: Dental and Oral Health, Elderly, Racial and Ethnic Minorities, Urban Health