Discovery of Risky Cases in Chronic Diseases: An Approach Using Trajectory Grouping
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This paper presents an approach to finding risky cases in chronic diseases using a trajectory grouping technique. Grouping of trajectories on hospital laboratory examinations is still a challenging task as it requires comparison of data with mutidimensionalty and temporal irregulariry. Our method first maps a set of time series containing different types of laboratory tests into directed trajectories representing the time course of patient states. Then the trajectories for individual patients are compared in multiscale and grouped into similar cases. Experimental results on the chronic hepatitis data demonstrated that the method could find the groups of discending trajectories that well corresponded to the cases of higher fibrotic stages.
KeywordsDissimilarity Matrix Segment Pair Perform Cluster Analysis Chronic Hepatitis Patient Segment Parameter
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