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Classifying patients into different risk groups based on their genomic measurements can help clinicians design appropriate clinical treatment plans. To produce such a classification, gene expression data were collected on a cohort of burn patients, who were monitored across multiple time points. This led us to develop a new classification method using time-course gene expressions. Our results showed that making good use of time-course information of gene expression improved the performance of classification compared with using gene expression from individual time points only. Our method is implemented into an R-package: time-course prediction analysis using microarray.