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machine learning methods, including cluster analysis and predictive modeling, to identify distinct phenotypes of diabetes and characterize factors associated with disease onset, progression, complications
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modeling techniques to identify patterns, trends, and emerging public health concerns. Design and evaluation of interactive data visualizations and dashboards to communicate scientific findings. Best
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, COMPASS-31 measures, etc. The project may include descriptive analysis, multivariable modeling, and integration of findings across epidemiologic datasets to improve understanding of infection-associated
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