ArticleStudies in health technology and informatics2016
A Data Mining Approach for Exploring Correlates of Self-Reported Comparative Physical Activity Levels of Urban Latinos.
Article in Studies in health technology and informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
We applied data mining techniques to a community-based behavioral dataset to build prediction models to gain insights about physical activity levels as the foundation for future interventions for urban Latinos. Our application of data mining strategies identified environment factors including having a convenient location for physical activity and psychological factors including depression as the strongest correlates of self-reported comparative physical activity among hundreds of variables. The data mining methods were useful to build prediction models to gain insights about perceptions of physical activity behavior as compared to peers.
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27332262PMC5504694What OpenQuestion holds
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