Adaptation Knowledge Acquisition: a Case Study for Case-Based Decision Support in Oncology

Mathieu d'Aquin 1, 2 Jean Lieber 1 Amedeo Napoli 1
1 ORPAILLEUR - Knowledge representation, reasonning
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : 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.
Document type :
Journal articles
Complete list of metadatas

Cited literature [27 references]  Display  Hide  Download

https://hal.inria.fr/inria-00116888
Contributor : Jean Lieber <>
Submitted on : Tuesday, November 28, 2006 - 3:49:02 PM
Last modification on : Friday, May 24, 2019 - 10:56:03 AM
Long-term archiving on : Tuesday, April 6, 2010 - 11:33:37 PM

File

daquin.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : inria-00116888, version 1

Collections

Citation

Mathieu d'Aquin, Jean Lieber, Amedeo Napoli. Adaptation Knowledge Acquisition: a Case Study for Case-Based Decision Support in Oncology. Computational Intelligence, Wiley, 2006, 22 (3/4), pp.161--176. ⟨inria-00116888⟩

Share

Metrics

Record views

328

Files downloads

599