Decentralized case-based reasoning and Semantic Web technologies applied to decision support in oncology - Inria - Institut national de recherche en sciences et technologies du numérique
Article Dans Une Revue Knowledge Engineering Review Année : 2013

Decentralized case-based reasoning and Semantic Web technologies applied to decision support in oncology

Mathieu d'Aquin
Jean Lieber
Amedeo Napoli

Résumé

This article presents the Kasimir system dedicated to decision knowledge management in oncology and which is built on top of Semantic Web technologies, taking benefit from standard knowledge representation formalisms and open reasoning tools. The representation of medical decision protocols, in particular for breast cancer treatment, is based on concepts and instances implemented within the description logic OWL DL. The knowledge units related to a protocol can then be applied for solving specific medical problems, using instance or concept classification. However, the straight application of a protocol is not always satisfactory, e.g., because of contraindications, necessitating an adaptation of the protocol. This is why the principles and methods of case-based reasoning in the framework of description logics have been used. In addition, the domain of oncology is complex and involves several specialties, e.g. surgery and chemotherapy. This complexity can be better undertaken with a viewpoint-based representation of protocols and viewpoint-based reasoning, for either application or adaptation of the protocols. Accordingly, a distributed description logic has been used for representing a viewpoint-based protocol. The application and the adaptation of the viewpoint-based protocol to medical cases is carried out using global instance classification and decentralized case-based reasoning.
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Dates et versions

hal-00922080 , version 1 (23-12-2013)

Identifiants

Citer

Mathieu d'Aquin, Jean Lieber, Amedeo Napoli. Decentralized case-based reasoning and Semantic Web technologies applied to decision support in oncology. Knowledge Engineering Review, 2013, 28 (4), pp.425--449. ⟨10.1017/S0269888913000027⟩. ⟨hal-00922080⟩
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