Granularity in Temporal Data Mining

Shoji Hirano and Shusaku Tsumoto.

This paper focuses on clustering of trajectories of temporal sequences of two laboratory examinations. First, we map a set of time series containing different types of laboratory tests into directed trajectories representing temporal change in patients’ status. Then the trajectories for individual patients are compared in multiscale and grouped into similar cases by using clustering methods.

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