Intelligent Clinical Decision Support Systems for Patient-Centered Healthcare in Breast Cancer Oncology

Authors: Nekane Larburu Rubio Naiara Muro Amuchastegui Mónica Arrúe Gabaráin

Date: 17.09.2018


Abstract

Breast cancer is the most common type of cancer in women worldwide, with incidence rate being second highest to other types of cancer. In the current clinical setting, multidisciplinary breast units are introduced to improve the quality of the therapeutic decision based on the best evidence-based practices. DESIREE project aims to provide a web-based software ecosystem for personalized, collaborative and multidisciplinary management of primary breast cancer by specialized breast units, from diagnosis to therapy and follow-ups. In order to provide a multi-model decision support to clinicians in present clinical settings, the project develops and integrates three modalities of decision support, namely guideline-based decision support system (DSS), experience-based DSS and case-based DSS. Visual analytics GUI are developed to properly adapt the results of the DSSs and graphically represent them to the clinician in a user-friendly manner. DESIREE information management system (DESIMS), serves as the interface between the user and DSSs for entering patient data and viewing the results in the visual analytics GUI. In this paper, we present the overall architecture, workflow and integration of the three DSSs in the DESIREE platform.

BIB_text

@Article {
title = {Intelligent Clinical Decision Support Systems for Patient-Centered Healthcare in Breast Cancer Oncology},
keywds = {
Breast cancer, guideline-based decision support system (DSS), experience-based DSS and case-based DSS
}
abstract = {

Breast cancer is the most common type of cancer in women worldwide, with incidence rate being second highest to other types of cancer. In the current clinical setting, multidisciplinary breast units are introduced to improve the quality of the therapeutic decision based on the best evidence-based practices. DESIREE project aims to provide a web-based software ecosystem for personalized, collaborative and multidisciplinary management of primary breast cancer by specialized breast units, from diagnosis to therapy and follow-ups. In order to provide a multi-model decision support to clinicians in present clinical settings, the project develops and integrates three modalities of decision support, namely guideline-based decision support system (DSS), experience-based DSS and case-based DSS. Visual analytics GUI are developed to properly adapt the results of the DSSs and graphically represent them to the clinician in a user-friendly manner. DESIREE information management system (DESIMS), serves as the interface between the user and DSSs for entering patient data and viewing the results in the visual analytics GUI. In this paper, we present the overall architecture, workflow and integration of the three DSSs in the DESIREE platform.


}
isbn = {978-1-5386-4294-8},
doi = {10.1109/HealthCom.2018.8531128},
date = {2018-09-17},
}
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