A Decision Support System for Diagnostics and Treatment Planning in Traumatic Brain Injury

Adil Umer, Jussi Mattila, Hilkka Liedes, Juha Koikkalainen, Jyrki Lotjonen, Ari Katila, Janek Frantzen, Virginia Newcombe, Olli Tenovuo, David Menon, Mark van Gils

    Research output: Contribution to journalArticleScientificpeer-review

    11 Citations (Scopus)


    Traumatic Brain Injury (TBI) occurs when an external force causes functional or structural alterations in the brain. Clinical characteristics of TBI vary greatly from patient to patient, and a large amount of data is gathered during various phases of clinical care in these patients. It is hard for clinicians to efficiently integrate and interpret all of these data and plan interventions in a timely manner. This paper describes the technical architecture and functionality of a web-based Decision Support System (DSS), which not only provides advanced support for visualizing complex TBI data but also predicts a possible outcome by using a state-of-the-art Disease State Index machine-learning algorithm. The DSS is developed by using a three-layered architecture and by employing modern programming principles, software design patterns and using robust technologies (C#, ASP.NET MVC, HTML5, JavaScript, and Entity Framework etc.). The DSS is comprised of a patient overview module, a disease-state prediction module and an imaging module. After deploying it on a web-server, the DSS was made available to two hospitals in UK and Finland. Afterwards, we conducted a validation study to evaluate its usability in clinical settings. Initial results of the study indicate that especially less experience clinicians may benefit from this type of decision support software tool.

    Original languageEnglish
    Article number8370619
    Pages (from-to)1261-1268
    JournalIEEE Journal of Biomedical and Health Informatics
    Issue number3
    Publication statusPublished - 1 May 2019
    MoE publication typeA1 Journal article-refereed


    • clinical decision support
    • Computer architecture
    • Data models
    • Data visualization
    • Decision support systems
    • Diseases
    • Hospitals
    • Imaging
    • traumatic brain injury
    • web-based tool


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