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

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.

• Publication year

  2018

• Venue

  International Conference on e-Health Networking, Applications and Services

• Publication date

  2018-09-01

• Fields of study

  Medicine, Computer Science

• Identifiers
  DOI 10.1109/HealthCom.2018.8531128
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Combining the Generic Entity-Attribute-Value Model and Terminological Models into a Common Ontology to Enable Data Integration and Decision Support

  2018cited by this paper
• Artificial Feeding Birds (AFB): A New Metaheuristic Inspired by the Behavior of Pigeons

  2018cited by this paper
• Reconciliation of multiple guidelines for decision support: a case study on the multidisciplinary management of breast cancer within the DESIREE project

  2017cited by this paper
• Rainbow boxes: A new technique for overlapping set visualization and two applications in the biomedical domain

  2017cited by this paper
• Drawing Conclusions from Linked Data on the Web: The EYE Reasoner

  2015cited by this paper
• Generation of knowledge for clinical decision support: Statistical and machine learning techniques

  2014cited by this paper
• NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines

  2014cited by this paper
• Bringing Big Data to Personalized Healthcare: A Patient-Centered Framework

  2013cited by this paper
• GLOBOCAN 2012: Estimated cancer incidence, mortality and prevalence worldwide in 2012

  2013cited by this paper
• Effect of Clinical Decision-Support Systems

  2012cited by this paper
• Applied Multidimensional Scaling

  2012cited by this paper
• ONCODOC: a successful experiment of computer-supported guideline development and implementation in the treatment of breast cancer

  2001cited by this paper

• Clinical Decision Support System Using Recurrent Neural Network

  2024cites this paper
• Supporting patients and clinicians during the breast cancer care path with AI: The Arianna solution

  2023cites this paper
• The Application of Data Science Techniques and Algorithms in Women Health Research

  2022cites this paper
• Information System for Screening and Automation of Document Management in Oncological Clinics

  2021cites this paper
• Supporting visual analytics in decision support system: a systematic mapping study

  2020cites this paper
• Breast Cancer Identification and Diagnosis Techniques

  2020cites this paper
• A Decision Support System for Therapy Prescription in a Hospital Centre

  2020cites this paper
• Explainable artificial intelligence for breast cancer: A visual case-based reasoning approach

  2019cites this paper
• Decision Support System of Best Teacher Selection using Method MOORA and SAW

  2019cites this paper