Authors: Shusaku Tsumoto; Shoji Hirano
Addresses: Department of Medical Informatics, School of Medicine, Faculty of Medicine, Shimane University, 89-1 Enya-cho, Izumo 693 8501, Japan ' Department of Medical Informatics, School of Medicine, Faculty of Medicine, Shimane University, 89-1 Enya-cho, Izumo 693 8501, Japan
Abstract: Since medical and healthcare data include temporal trends of clinical symptoms, temporal data mining is one of the most important elements to discover knowledge. In this paper, we propose a three-dimensional trajectories mining method to capture the similarities between temporal trajectories of three selected variables. The method was evaluated on two datasets: one is on chronic hepatitis, and the other is on temporal trends of # orders in our university hospital. The results showed that, compared with conventional studies, the method gave more detailed classification of temporal trends.
Keywords: temporal data mining; clustering; hospital information system; HIS; visualisation.
International Journal of Computational Intelligence Studies, 2016 Vol.5 No.3/4, pp.317 - 337
Received: 21 Nov 2015
Accepted: 25 Jan 2016
Published online: 11 Apr 2017 *