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Updated: Feb 9, 2026

Long-term Culture of Human Breast Cancer Specimens and Their Analysis Using Optical Projection Tomography
Published on: July 29, 2011
Reconciliation of multiple guidelines for decision support: a case study on the multidisciplinary management of
Brigitte Séroussi1,2,3, Gilles Guézennec1, Jean-Baptiste Lamy1
1Sorbonne Universités, UPMC Univ Paris 06, INSERM, Université Paris 13, Sorbonne Paris Cité, UMRS 1142, LIMICS, Paris, France.
Abstract:
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.
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