Breast cancer is the most common cancer among women. DESIREE is a European project which aims at developing web-based services for the management of primary breast cancer by multidisciplinary breast units (BUs). We describe the guideline-based decision support system (GL-DSS) of the project. Various breast cancer clinical practice guidelines (CPGs) have been selected to be concurrently applied to provide state-of-the-art patient-specific recommendations. The aim is to reconcile CPG recommendations with the objective of complementarity to enlarge the number of clinical situations covered by the GL-DSS. Input and output data exchange with the GL-DSS is performed using FHIR. We used a knowledge model of the domain as an ontology on which relies the reasoning process performed by rules that encode the selected CPGs. Semantic web tools were used, notably the Euler/EYE inference engine, to implement the GL-DSS. "Rainbow boxes" are a synthetic tabular display used to visualize the inferred recommendations.
|Title of host publication||AMIA Annual Symposium Proceedings|
|Publication status||E-pub ahead of print - 8 Nov 2017|
|Event||AMIA Annual Symposium 2017 - Washington DC, United States|
Duration: 4 Nov 2017 → 8 Nov 2017
|Conference||AMIA Annual Symposium 2017|
|Period||4/11/17 → 8/11/17|
Seroussi, B., Guézennec, G., Lamy, J-B., Muro, N., Larburu, N., Sekar, B., ... Bouaud, J. (2017). Reconciliation of Multiple Guidelines for Decision Support: A case study on the multidisciplinary management of breast cancer within the DESIREE project. In AMIA Annual Symposium Proceedings (pp. 1527-1536)