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An interpretable machine learning model of cross-sectional U.S. county-level obesity prevalence using explainable artificial intelligence
BACKGROUND: There is considerable geographic heterogeneity in obesity prevalence across counties in the United States. Machine learning algorithms accurately predict geographic variation in obesity prevalence, but the models are often uninterpretable and viewed as a black-box. OBJECTIVE: The goal of...
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Public Library of Science
2023
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10553328/ https://www.ncbi.nlm.nih.gov/pubmed/37796874 http://dx.doi.org/10.1371/journal.pone.0292341 |