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Adaptation knowledge acquisition: a case study for case-based decision support in oncology

D'Aquin, Mathieu; Lieber, Jean and Napoli, Amedeo (2006). Adaptation knowledge acquisition: a case study for case-based decision support in oncology. Computational Intelligence, 22(3/4) pp. 161–176.

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KASIMIR is a case-based decision support system in the domain of breast cancer treatment. For this system, a problem is given by the description of a patient and a solution is a set of therapeutic decisions. Given a target problem, KASIMIR provides several suggestions of solutions, based on several justified adaptations of source cases. Such adaptation processes are based on adaptation knowledge. The acquisition of this kind of knowledge from experts is presented in this paper. It is shown how the decomposition of adaptation processes by introduction of intermediate problems can highlight simple and generalizable adaptation steps. Moreover, some adaptation knowledge units that are generalized from the ones acquired for KASIMIR are presented. This knowledge can be instantiated in other case- based decision support systems, in particular in medicine.

Item Type: Journal Article
Copyright Holders: 2006 Blackwell Publishing
ISSN: 1467-8640
Keywords: case-based decision support;adaptation;knowledge acquisition;breast cancer treatment;medical informatics
Academic Unit/Department: Knowledge Media Institute
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 24328
Depositing User: Mathieu d'Aquin
Date Deposited: 30 Mar 2011 13:11
Last Modified: 25 Feb 2016 04:32
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