Currently, international clinical guidelines (CG), provide an evidence-based knowledge approach to the management of breast cancer. However, CG reported in the state-of-the-art neither address the uncertainty in decision making related to the applicability of trials to individual patients nor the uncertainty due to patient preferences on outcomes and treatment risks. For these reasons computerized decision support systems (CDSS) incorporate predictive models for diagnosis, treatment and outcomes in the breast cancer management workflow, providing a unified framework for uncertainty management in clinical guidelines. These predictive models would provide adjuvant evidence to the stakeholders in specific questions of special relevance during the decision-making process in the management the breast cancer, ultimately allowing effective communication of risk and patient preference's elicitation. The purpose of this project is to assess the clinical impact of CDSS on breast cancer diagnosis and treatment.