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Implementing Guideline-Based, Experience-Based, and Case-Based Approaches to Enrich Decision Support for the Management of Breast Cancer Patients in the DESIREE Project

Seroussi, B ; Lamy, Jb ; Muro, N ; Larburu, N ; Sekar, Bd ; Guézennec, G ; Bouaud, J

Studies in health technology and informatics, 2018, Vol.255, p.190-194 [Revista revisada por pares]

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Título:
Implementing Guideline-Based, Experience-Based, and Case-Based Approaches to Enrich Decision Support for the Management of Breast Cancer Patients in the DESIREE Project
Autor: Seroussi, B ; Lamy, Jb ; Muro, N ; Larburu, N ; Sekar, Bd ; Guézennec, G ; Bouaud, J
Materias: Bioinformatics ; Computer Science
Es parte de: Studies in health technology and informatics, 2018, Vol.255, p.190-194
Descripción: DESIREE is a European-funded project to improve the management of primary breast cancer. We have developed three decision support systems (DSSs), a guideline-based, an experience-based, and a case-based DSSs, resp. GL-DSS, EXP-DSS, and CB-DSS, that operate simultaneously to offer an enriched multi-modal decision support to clinicians. A breast cancer knowledge model has been built to describe within a common ontology the data model and the termino-ontological knowledge used for representing breast cancer patient cases. It allows for rule-based and subsumption-based reasoning in the GL-DSS to provide best patient-centered reconciled care plans. It also allows for using semantic similarity in the retrieval algorithm implemented in the CB-DSS. Rainbow boxes are used to display patient cases similar to a given query patient. This innovative visualization technique translates the question of deciding the most appropriate treatment into a question of deciding the colour dominance among boxes.
Editor: IOS Press
Idioma: Inglés

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