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Joint models for longitudinal biomarkers and time-to-event data are widely used in longitudinal studies. Many joint modeling approaches have been proposed to handle different types of longitudinal biomarkers and survival outcomes. However, most existing joint modeling methods cannot deal with a large number of longitudinal biomarkers simultaneously, such as the longitudinally collected gene expression...
Subgroup identification (clustering) is an important problem in biomedical research. Gene expression profiles are commonly utilized to define subgroups. Longitudinal gene expression profiles might provide additional information on disease progression than what is captured by baseline profiles alone. Therefore, subgroup identification could be more accurate and effective with the aid of longitudinal...
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