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There are many outbreak detection that available with various techniques being introduced ranging from statistic to data mining including machine learning. With the direction of spatial-temporal data the research under public health surveillance especially outbreak detection or anomalies detection are promising research. In this paper, the authors applied data mining techniques in detecting outbreak in public health surveillance. The phase involves learning, detecting and repository. An extracted sequential pattern method, outlier set was identified using outlier detection algorithm methods.
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