Digital Health Europe

DESIREE: a holistic web-based software ecosystem for the management of primary breast cancer

Keywords: (Clinical) Decision Support Services, Cancer, Management
Short description
DESIREE provides a web-based software ecosystem for the personalized, collaborative and multidisciplinary management of primary breast cancer (PBC) by specialized Breast Units. Decision support will be provided on the available therapy options by incorporating experience from previous cases and outcomes into an evolving knowledge model, going beyond the limitations of the few existing guideline-based decision support systems (DSS). Patient cases will be represented by a novel digital breast cancer patient (DBCP) data model, incorporating variables relevant for decision and novel sources of information and biomarkers of diagnostic and prognostic value, providing a holistic view of the patient presented to the BU through specialized visual exploratory interfaces. The influence of new variables and biomarkers in current and previous cases will be explored by a set of data mining and visual analytics tools, leveraging large amounts of retrospective data. Iintuitive web-based tools for multi-modality image analysis and fusion will be developed, providing advanced imaging biomarkers for breast and tumor characterization. Finally, a predictive tool for breast conservative therapy will be incorporated, based on a multi-scale physiological model, allowing to predict the aesthetic outcome of the intervention and the healing process, with important clinical and psychological implications for the patients.
Proof of concept is available: it works in a test setting and the potential end-users are positive about the concept 
Geographical scope
Submitted in other database or repository of digital health resources that is publicly available, DHE catalogue

Additional information

to clinicians / care practitioners
Clinical decision support
Health data analytics (Artificial Intelligence/algorithm development and calibration/machine learning/risk stratification tools/etc.)
Virtual reality surgery
Primary target patient group (age)
Adults (25-64), Older adults (65+)
Use case and care pathway positioning
Early detection and early diagnosis, precision diagnosis, Reuse of data for research