Modeling adaptation of breast cancer treatment decision protocols in the Kasimir project

  • Authors:

  • Jean Lieber;Mathieu D'Aquin;Fadi Badra;Amedeo Napoli

  • Affiliations:

  • Orpailleur team, LORIA (UMR 7503 CNRS-INPL-INRIA-Nancy 2-UHP), Vandoeurve-les-Nancy, France 54 506;Orpailleur team, LORIA (UMR 7503 CNRS-INPL-INRIA-Nancy 2-UHP), Vandoeurve-les-Nancy, France 54 506 and Knowledge Media Institute (KMi), The Open University, Milton Keynes, UK;Orpailleur team, LORIA (UMR 7503 CNRS-INPL-INRIA-Nancy 2-UHP), Vandoeurve-les-Nancy, France 54 506;Orpailleur team, LORIA (UMR 7503 CNRS-INPL-INRIA-Nancy 2-UHP), Vandoeurve-les-Nancy, France 54 506

  • Venue:
  • Applied Intelligence
  • Year:
  • 2008

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Abstract

Medical decision protocols constitute theories for health-care decision making that are applicable for "standard" medical cases but have to be adapted for the other cases. This holds in particular for the breast cancer treatment protocol studied in the Kasimir research project. Protocol adaptations can be seen as knowledge-intensive case-based decision support processes. Some examples of adaptations that have been performed by oncologists are presented in this paper. Several issues are then identified that need to be addressed while trying to model such processes, namely: the complexity of adaptations, the lack of relevant information about the patient, the necessity to take into account the applicability and the consequences of a decision, the closeness to decision thresholds, and the necessity to consider some patients according to different viewpoints. As handling these issues requires some additional knowledge, which has to be acquired, different methods are presented that perform adaptation knowledge acquisition either from experts, or in a semi-automatic manner. A discussion and a conclusion end the paper.