• DocumentCode
    265119
  • Title

    Automating the Integration of Clinical Studies into Medical Ontologies

  • Author

    Roantree, Mark ; O´Donoghue, Jim ; O´Kelly, Noel ; van Boxtel, Martin ; Kohler, Sophie

  • Author_Institution
    Sch. of Comput., Dublin City Univ., Dublin, Ireland
  • fYear
    2014
  • fDate
    6-9 Jan. 2014
  • Firstpage
    2938
  • Lastpage
    2947
  • Abstract
    A popular approach to knowledge extraction from clinical databases is to first define an ontology of the concepts one wishes to model and subsequently, use these concepts to test various hypotheses and make predictions about a person´s future health and well being. The challenge for medical experts is in the time taken to map between their concepts/hypotheses and information contained within clinical studies. Presently, most of this work is performed manually. We have developed a method to generate links between Risk Factors in a medical ontology and the questions and result data in longitudinal studies. This can then be exploited to express complex queries based on domain concepts, to extract knowledge from external studies.
  • Keywords
    knowledge acquisition; medical information systems; ontologies (artificial intelligence); risk analysis; clinical databases; clinical studies; complex queries; domain concepts; external studies; future health; future wellbeing; integration automation; knowledge extraction; longitudinal studies; medical experts; medical ontologies; risk factors; Cognition; Data mining; Databases; Dementia; Educational institutions; Ontologies; Vocabulary;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Sciences (HICSS), 2014 47th Hawaii International Conference on
  • Conference_Location
    Waikoloa, HI
  • Type

    conf

  • DOI
    10.1109/HICSS.2014.366
  • Filename
    6758966