Adaptation and Medical Case-Based Reasoning Focusing on Endocrine Therapy Support

Vorobieva, Olga

doi:10.1007/11527770_42

Cited by 8 publications

(2 citation statements)

References 16 publications

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“…In medical CBR systems, adaptation has often a key role to play, as argued in [39], in which several kinds of adaptations are presented. One of them is constituted by "adaptation operators or rules", that confront the issue of a knowledge acquisition bottleneck.…”

Section: Related Work In Medical Cbrmentioning

confidence: 99%

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

et al. 2007

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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 J. Lieber ( ) · M. d'Aquin · F. Badra · A. Napoli Orpailleur team, LORIA (UMR 7503 CNRS-INPL-INRIA-Nancy 2-UHP), BP 239, 54 506,

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Section: Related Work In Medical Cbrmentioning

confidence: 99%

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

et al. 2007

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“…That is why explanations have been associated to the adaptation knowledge that is acquired for Kasimir. In these medical CBR systems, adaptation has often a key role to play, as argued in (Schmidt & Vorobieva, 2005), in which several kinds of adaptations are presented. One of them is constituted by "adaptation operators or rules", that are confronted to the issue of knowledge acquisition bottleneck.…”

Section: Related Work In Medical Cbrmentioning

confidence: 99%

Adaptation Knowledge Acquisition: A Case Study for Case‐based Decision Support in Oncology

d’Aquin

Lieber

Napoli

2006

Computational Intelligence

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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 casebased decision support systems, in particular in medicine.

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Discriminative Distance Functions and the Patient Neighborhood Graph for Clinical Decision Support

Tsymbal

Huber²,

Zhou³

2010

Advances in Experimental Medicine and Biology

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There are two essential reasons for the slow progress in the acceptance of clinical similarity search-based decision support systems (DSSs); the especial complexity of biomedical data making it difficult to define a meaningful and effective distance function and the lack of transparency and explanation ability in many existing DSSs. In this chapter, we address these two problems by introducing a novel technique for visualizing patient similarity with neighborhood graphs and by considering two techniques for learning discriminative distance functions. We present an experimental study and discuss our implementation of similarity visualization within a clinical DSS.

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Adaptation and Medical Case-Based Reasoning Focusing on Endocrine Therapy Support

Cited by 8 publications

References 16 publications

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

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

Adaptation Knowledge Acquisition: A Case Study for Case‐based Decision Support in Oncology

Discriminative Distance Functions and the Patient Neighborhood Graph for Clinical Decision Support

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