You are required to read and agree to the below before accessing a full-text version of an article in the IDE article repository.

The full-text document you are about to access is subject to national and international copyright laws. In most cases (but not necessarily all) the consequence is that personal use is allowed given that the copyright owner is duly acknowledged and respected. All other use (typically) require an explicit permission (often in writing) by the copyright owner.

For the reports in this repository we specifically note that

  • the use of articles under IEEE copyright is governed by the IEEE copyright policy (available at http://www.ieee.org/web/publications/rights/copyrightpolicy.html)
  • the use of articles under ACM copyright is governed by the ACM copyright policy (available at http://www.acm.org/pubs/copyright_policy/)
  • technical reports and other articles issued by M‰lardalen University is free for personal use. For other use, the explicit consent of the authors is required
  • in other cases, please contact the copyright owner for detailed information

By accepting I agree to acknowledge and respect the rights of the copyright owner of the document I am about to access.

If you are in doubt, feel free to contact webmaster@ide.mdh.se

Knowledge Discovery and Case Based Reasoning in Medical Applications with Time Series

Publication Type:

Conference/Workshop Paper

Venue:

In Workshop proceedings of the 6th International Conference on Case Based Reasoning


Abstract

This paper discusses the role and integration of knowledge discovery in case based reasoning systems. The general view is that knowledge discovery is complementary to the task of knowledge retaining and it can be treated as a separate process outside the traditional CBR cycle. Unlike knowledge retaining which is mostly related to case-specific experience, knowledge discovery aims at the elicitation of new knowledge that is more general and valuable by im-proving the functionality of the different CBR sub-steps. The importance of knowledge discovery for CBR is exemplified by a real application scenario in stress medicine in which time series of patterns of breathing cycles are to be analyzed and classified. As single breathing patterns cannot convey reliable in-formation, sequences of patterns are deemed more adequate evidence for diag-nosis by experts. Hence it is advantageous if sequences of patterns can be iden-tified in a CBR approach to a diagnosis and co-occurrence is discovered in categories of patients with similar status.

Bibtex

@inproceedings{Funk812,
author = {Peter Funk and Markus Nilsson and Ning Xiong},
title = {Knowledge Discovery and Case Based Reasoning in Medical Applications with Time Series},
editor = {Isabelle Bichindaritz, Cindy Marling},
month = {December},
year = {2005},
booktitle = {In Workshop proceedings of the 6th International Conference on Case Based Reasoning},
url = {http://www.es.mdh.se/publications/812-}
}