• DocumentCode
    3715668
  • Title

    An ontological-based monitoring system for patients with bipolar I disorder

  • Author

    Chryssa H. Thermolia;Ekaterini S. Bei;Euripides G. M. Petrakis;Vangelis Kritsotakis;Vangelis Sakkalis

  • Author_Institution
    School of Electronic and Computer Engineering Technical University of Crete 73100 Chania, Crete, Hellas
  • fYear
    2015
  • Firstpage
    43
  • Lastpage
    49
  • Abstract
    Our aim is to provide a patient monitoring system that integrates a Clinical Decision Support System (CDSS) and an Electronic Health Record (EHR) that assist psychiatrists and primary care physicians to tackle existent health needs of mental illness related to the treatment and management of bipolar I disorder (BDI). Our monitoring system consists of an EHR system based on the Health Level Seven Reference Information Model (HL 7-RIM) and an ontological-based CDSS leveraging the Semantic Web capabilities. Based on the evidence-based clinical guidelines and patients´ health records, the monitoring system is developed to encode and process this information and subsequently to assign recommendations of choices and alerts to clinicians for improved mental health care. Considering the clinical guidelines germane knowledge, as well as issues of patient´s health record, the monitoring system can support a personalized decision-making for bipolar I disorder longitudinal course. We propose AI-CARE as an online monitoring tool that may offer useful guidance in clinical practice.
  • Keywords
    "Ontologies","Monitoring","Medical diagnostic imaging","Guidelines","Medical treatment","Semantic Web"
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Computational Technologies (SIBIRCON), 2015 International Conference on
  • Print_ISBN
    978-1-4673-9109-2
  • Type

    conf

  • DOI
    10.1109/SIBIRCON.2015.7361847
  • Filename
    7361847