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A Computer Aided System for Post-operative Pain Treatment Combining Knowledge Discovery and Case-Based Reasoning

Authors:

Mobyen Uddin Ahmed, Peter Funk

Research group:

Artificial Intelligence and Intelligent Systems

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-}
}