DESIREE DEMO - A Web-Based Software Ecosystem for the Personalized, Collaborative and Multidisciplinary Management of Primary Breast Cancer

Abstract

Breast cancer is the most overspread cancer in women worldwide, with around 1.7 million new cases every year. Multidisciplinary clinical teams or committees, usually known as Breast Units (BU), are heterogeneous teams composed by all clinical specialist involved in the care of a breast cancer patient (e.g. oncologist, surgeon, …) that aim to discuss these complex clinical cases from all points of view and in the shortest time to provide best health care. BUs base their decisions on the Clinical Practice Guidelines (CPGs), documents that summarize the latest and best evidence-based medicine. Nevertheless, these documents have some knowledge lacks that make them insufficient when working with complex cases "out of the rule", that may represent the 10-20% of the cases. To cope with this pitfall, DESIREE proposes a unified ecosystem that manages all the relevant information of the patients and provides support to clinicians when making a clinical decision in a personalized, collaborative and multidisciplinary way. It is composed by three main components: (i) an image-based breast and tumor characterization tool, (ii) a predictive model after breast conservative therapy and radio-biological model, and (iii) three different clinical decision support systems (i.e. guideline-based, experience-based and patient similarity based) that coexist and complement each other to give most personalized and best evidence-based recommendations to the BUs. All these are supported by DESIMS (i.e. DESiree Information Management System), a Security and Access Control module and an image system for image and models visualization.

Automated Clinical Practice Guideline Recommendations for Hereditary Cancer Risk Using Chatbots and Ontologies: System Description

“…Clinical workflow integration primarily supports clinicians and is generally less accessible to patients. DESIREE (Decision Support and Information Management System for Breast Cancer) is a more recent example of such a solution that uses ontological reasoning to support CPG application to patients with breast cancer in clinical settings to help tumor boards develop care plans [ 55 - 57 ]. Similar to our system, DESIREE and SAGE used Protégé to develop domain ontologies to computerize CPGs.…”