Title :
Trajectory mining using multiscale matching and clustering
Author :
Hirano, Shoji ; Tsumoto, Shusaku
Author_Institution :
Dept. of Med. Inf., Shimane Univ., Izumo
Abstract :
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 patientspsila status. Then the trajectories for individual patients are compared in multiscale and grouped into similar cases by using clustering methods. Experimental results on the chronic hepatitis data demonstrated that the method could find the groups of trajectories which reflects temporal covariance of platelet, albumin and choline esterase.
Keywords :
covariance analysis; medical information systems; pattern clustering; time series; chronic hepatitis data; multiscale clustering; multiscale matching; temporal covariance; temporal sequences; time series; trajectory mining; Clustering methods; Databases; Electronic equipment testing; Laboratories; Liver diseases; Medical tests; System testing; Time measurement; Time series analysis; Trajectory;
Conference_Titel :
Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1818-3
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2008.4630707