• DocumentCode
    2199730
  • Title

    Ontology based EMR for decision making in health care using SNOMED CT

  • Author

    Julina, J. Kulandai Josephine ; Thenmozhi, D.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., SSN Coll. of Eng., Chennai, India
  • fYear
    2012
  • fDate
    19-21 April 2012
  • Firstpage
    514
  • Lastpage
    519
  • Abstract
    Health care domain is gaining more focus in the field of Ontology and Semantic research. Ontology in medicine helps in proper representation and organization of clinical terminologies. An Electronic Medical Record (EMR) based on Ontology plays a significant role in decision making process. However there is a lack of standards in constructing Ontology, based on the current needs of the healthcare professionals, which results in poor quality of information extraction. This paper proposes the use of Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), an existing medical Ontology which can be restructured to a high quality Ontology for achieving efficient information extraction. An EMR captures accurate patient information based on enriched Ontology thereby making it suitable for decision making with the help of Bayesian Belief approach.
  • Keywords
    belief networks; decision making; decision support systems; health care; information retrieval; medical information systems; ontologies (artificial intelligence); Bayesian belief approach; Bayesian network; SNOMED CT; clinical terminologies; decision making process; electronic medical record; health care; information extraction; medical ontology based EMR; systematized nomenclature-of-medicine clinical terms; Bayesian methods; Decision making; Diseases; Lungs; Ontologies; Semantics; Bayesian Network; Electronic Medical Record; Health Care; Lung Diseases; Ontology; SNOMED CT;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Recent Trends In Information Technology (ICRTIT), 2012 International Conference on
  • Conference_Location
    Chennai, Tamil Nadu
  • Print_ISBN
    978-1-4673-1599-9
  • Type

    conf

  • DOI
    10.1109/ICRTIT.2012.6206787
  • Filename
    6206787