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A Computer Aided System for Post-operative Pain Treatment Combining Knowledge Discovery and Case-Based Reasoning
Publication Type:
Conference/Workshop Paper
Venue:
International Conference on Case-Based Reasoning
Abstract
The quality improvement for individual postoperative-pain treatment is an
important issue. This paper presents a computer aided system for physicians in their
decision making tasks in post-operative pain treatment. Here, the system combines a
Case-Based Reasoning (CBR) approach with knowledge discovery. Knowledge
discovery is applied in terms of clustering in order to identify the unusual cases. We
applied a two layered case structure for case solutions i.e. the treatment is in the first
layer and outcome after treatment (i.e. recovery of the patient) is in the second layer.
Moreover, a 2nd order retrieval approach is applied in the CBR retrieval step in order
to retrieve the most similar cases. The system enables physicians to make more
informed decisions since they are able to explore similar both regular and rare cases
of post-operative patients. The two layered case structure is moving the focus from
diagnosis to outcome i.e. the recovery of the patient, something a physician is
especially interested in, including the risk of complications and side effects.
Bibtex
@inproceedings{Ahmed2494,
author = {Mobyen Uddin Ahmed and Peter Funk},
title = {A Computer Aided System for Post-operative Pain Treatment Combining Knowledge Discovery and Case-Based Reasoning },
month = {September},
year = {2012},
booktitle = {International Conference on Case-Based Reasoning},
url = {http://www.es.mdu.se/publications/2494-}
}