Multidimensional temporal mining in hospital information system
by Shusaku Tsumoto; Shoji Hirano
International Journal of Computational Intelligence Studies (IJCISTUDIES), Vol. 5, No. 3/4, 2016

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.

Online publication date: Tue, 11-Apr-2017

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Intelligence Studies (IJCISTUDIES):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com