Case-Based Decision Support System for Breast Cancer Management

Booma Sekar 1 Jean-Baptiste Lamy 2, 3 Nekane Larburu 4 Brigitte Séroussi 2, 3, 5 Gilles Guezennec 2, 3 Jacques Bouaud 2, 3, 6 Naiara Muro 2, 3, 4 Hui Wang 1 Jun Liu 1
1 University of Ulster
2 LIMICS - Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en e-Santé
3 USPC - Université Sorbonne Paris Cité
4 Vicomtech-IK4 [San Sebastián]
5 Service de Santé Publique [CHU Tenon]
6 DRCI - Délégation à la recherche clinique et à l'innovation [CHU Dijon]
Abstract : Breast cancer is identified as the most common type of cancer in women worldwide with 1.6 million women around the world diagnosed every year. This prompts many active areas of research in identifying better ways to prevent, detect, and treat breast cancer. DESIREE is a European Union funded project, which aims at developing a web-based software ecosystem for the multidisciplinary management of primary breast cancer. The development of an intelligent clinical decision support system offering various modalities of decision support is one of the key objectives of the project. This paper explores case-based reasoning as a problem solving paradigm and discusses the use of an explicit domain knowledge ontology in the development of a knowledge-intensive case-based decision support system for breast cancer management.
Keywords : jColibri case-based decision support system ontology breast cancer knowledge intensive case-based reasoning
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SORBONNE-UNIVERSITE | UNIV-PARIS13 | LIMICS | SU-SCIENCES | USPC

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Booma Sekar, Jean-Baptiste Lamy, Nekane Larburu, Brigitte Séroussi, Gilles Guezennec, et al.. Case-Based Decision Support System for Breast Cancer Management. International Journal of Computational Intelligence Systems, Atlantis Press, 2018, 12 (1), pp.28-38. ⟨10.2991/ijcis.2018.25905180⟩. ⟨hal-02289438⟩

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