By Topic

Strucutural Comparison and Cluster Analysis of Time-Series Medical Data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
S. Hirano ; Department of Medical Informatics, Shimane University, School of Medicine 89-1 Enya-cho, Izumo, Shimane 693-8501, Japan ; S. Tsumoto

In this paper we present a cluster analysis scheme for time series medical data. It allows us the structural comparison and hierarchical grouping of irregularly-sampled, irregular-length time series. The core technique is modified multiscale matching, which improves the segment parameter representation and dissimilarity measures in the multiscale structure matching so that the problem of shrinkage and mixture of multiple attributes in the dissimilarity can be solved. We examined the usefulness of the method on the platelet sequences in the chronic hepatitis dataset. The results demonstrated that the dissimilarity matrix produced by the proposed method, combined with conventional clustering techniques, lead to the successful clustering for both synthetic and real-world data

Published in:

2005 IEEE International Conference on Systems, Man and Cybernetics  (Volume:2 )

Date of Conference:

12-12 Oct. 2005